Green growth? A consumption perspective on Swedish ...436275/FULLTEXT01.pdf · Abstract Green...

Green growth?A consumption perspective on Swedish

environmental impact trends using

Mårten Berglund

Grön tillväxt? Svensk miljöpåverkan ur ett

konsumtionsperspektiv med tillämpning av

UPTEC W11 021

Examensarbete 30 hpJuni 2011

input–output analysis

input–output-analys

Abstract

Green growth? A consumption perspective on Swedish environmentalimpact trends using input–output analysis

Marten Berglund

Consumption-based environmental impact trends for the Swedish economy havebeen generated and analysed in order to determine their levels compared to officialproduction-based data, and to determine whether or not the Swedish economy hasdecoupled growth in domestic final demand from worldwide environmental impact.Three energy resources (oil, coal and gas use, as well as their aggregate fossil fueluse) and seven emissions (CO2, CH4, N2O, SO2, NOx, CO and NMVOC, as wellas the aggregate CO2 equivalents) were studied. An augmented single-regionalinput–output model has been deployed, with world average energy and emissionintensities used for products produced abroad. A new method for updating input–output tables for years missing official input–output tables, was also developed.For each of the resources and the emissions, two time series were generated basedon two different revisions of Swedish national accounts data, one for the period1993–2003, the other for the period 2000–2005. The analysis uses a recently re-vised time series of environmental data from the Swedish environmental accounts,as well as recently published global environmental data from the IEA and fromthe EDGAR emissions database (all data from 2010 or later). An index decompo-sition analysis was also performed to detect the various components of the timeseries. For fossil fuels consumption-based data don’t differ much from production-based data in total. For the greenhouse gases there is a clear increase (CO2eqemissions increase approximately 20 % from 1993–2005, mainly driven by an in-crease in CH4 emissions), resulting from increased emissions abroad due to theincreased demand for imported products. This suggests Sweden has not decoupledeconomic growth from increasing greenhouse gas emissions – contrary to what theslightly decreasing official production-based UNFCCC data say. For the precursorgases (SO2, NOx, CO and NMVOC), emissions are generally decreasing, with theexception of SO2 and NOx which increase in the second time series. For all emis-sions studied, consumption-based data lie at much higher levels than the officialproduction-based UNFCCC data. However, further research is needed regardingthe resolution of the data of the energy use and the emissions generated abroadby the Swedish domestic final demand. Also, extension of the time series and ofthe environmental parameters to such things as material use is needed to find outwith more certainty to what extent Swedish growth has been sustainable or not.

Keywords: Input–output analysis, emissions embodied in trade, environmentalKuznets curve, index decomposition analysis, green growth, IPAT equation, car-bon footprint, consumption-based accounting, fossil fuels, greenhouse gases, atmo-spheric pollution, Sweden.

Global Energy Systems, Department of Physics and Astronomy,Uppsala University, Box 516, SE-751 20 Uppsala, Sweden

ISSN 1401-5765

iii

Referat

Gron tillvaxt? Svensk miljopaverkan ur ett konsumtionsperspektiv medtillampning av input–output-analys

Marten Berglund

I den har studien har konsumtionsbaserade tidsserier pa svensk fossilbranslean-vandning och pa svenska utslapp av luftfororeningar tagits fram i avsikt att jam-fora dessa med de officiella produktionsbaserade tidsserierna. Syftet har varit attavgora om det svenska samhallets paverkan pa resurser och miljo ur ett konsum-tionsperspektiv har minskat eller okat over tiden, och framforallt om en frikopplinghar skett mellan den svenska ekonomiska tillvaxten och den paverkan Sverige harpa miljon i Sverige och utomlands. Tre fossila branslen (olja, kol, gas samt aggre-gatet fossila branslen) och sju luftfororeningar (CO2, CH4, N2O, SO2, NOx, COoch NMVOC samt aggregatet CO2-ekvivalenter) har analyserats. En enkelregion-al input–output-modell har tagits fram, utokad med globala medelintensiteter forden produktion som sker utanfor Sverige. En ny metod har ocksa utvecklats foratt generera input–output-tabeller for ar dar officiella sadana tabeller saknas. Forsamtliga energiresurser och luftfororeningar, upprattades tva stycken tidsserier,baserat pa tva olika revisioner av ekonomiska data fran nationalrakenskaperna.Den forsta tidsserien tacker aren 1993–2003, och den andra aren 2000–2005. Miljo-data togs fran nyligen reviderade tidsserier fran de svenska miljorakenskapernasamt fran IEA och den internationella luftfororeningsdatabasen EDGAR (alla da-ta reviderade 2010 eller senare). En komponentanalys utfordes ocksa, for att iden-tifiera olika bidragande komponenter i tidsserierna. Vad galler fossila branslen isin helhet, uppstar ingen markant skillnad mellan konsumtionsbaserade och pro-duktionsbaserade data. Vad galler vaxthusgaserna kan en klar okning urskiljas(20 procents okning av CO2-ekvivalenter mellan 1993–2005; CH4-utslappen hardar bidragit mest), vilket beror pa stigande utslapp utomlands orsakade av okadefterfragan pa importerade produkter. Detta antyder att den svenska tillvaxtenannu inte frikopplats fran okade utslapp av vaxthusgaser, vilket star i motsatstill den minskning i utslapp som de officiella produktionsbaserade siffrorna franUNFCCC-rapporteringen redovisar. For ovriga luftfororeningar (SO2, NOx, COoch NMVOC), sker i allmanhet en minskning, forutom for SO2 och NOx som okari den andra tidsserien. Samtliga luftfororeningar ligger vidare pa en betydligt hogreniva jamfort med UNFCCC-rapporteringen. Mer detaljerade studier behovs dockpa den energiforbrukning och de utslapp som svensk slutlig anvandning for medsig utomlands. Tidsserierna behover ocksa forlangas och fler miljovariabler somt.ex. materialanvandningen behover studeras for att kunna dra sakrare slutsatserkring i vilken utstrackning som den svenska tillvaxten har varit hallbar eller ej.

Nyckelord : Input–output-analys, inbaddade utslapp, miljo-Kuznetskurvan,komponentanalys, gron tillvaxt, IPAT, kolavtryck, konsumtionsbaserad bokforing,fossila branslen, vaxthusgaser, luftfororeningar, Sverige.

Globala energisystem, Institutionen for fysik och astronomi, Uppsala universitet,Box 516, 751 20 Uppsala

ISSN 1401-5765

iv

Preface

This study is the result of a degree project within the Aquatic and Environ-mental Engineering Programme at Uppsala University. It has been performed atthe Global Energy Systems group at the Department of Physics and Astronomy.Supervisor has been Kristofer Jakobsson, and reviewer has been professor KjellAleklett, both at the Global Energy Systems group.

At first I’d like to thank my professor Kjell Aleklett who approved my proposal fordoing a study in the field of economic growth versus the environment within hisgroup. The next thanks goes of course to my supervisor Kristofer Jakobsson, whojust happened to possess a vast number of books in the subject of input–outputanalysis which again happened to be the main method used in this field – thanksfor all interesting discussions and for your support, patience and all encouragingwords during the project. I’d also like to thank Mikael Hook in the group forinteresting discussions and help.

People outside the group who need special mention, are Anders Wadeskog,Ann-Marie Brathen and Ida Bjork at the environmental accounts and nationalaccounts units of Statistics Sweden, who helped me a lot with the details of theinput–output tables. Glen Peters at CICERO in Oslo gave me good introduc-ing articles in the field of environmental input–output analysis and Pontus vonBromssen at Skandia Liv was helpful in checking some of the maths. I’d also liketo direct a special thanks to the librarians at the university library, who purchasedbooks and databases I’ve asked for, and for being generally helpful.

Finally, I’d like to thank my family and all friends who have been supporting mewith encouraging talks and interesting discussions without which all my thoughtsabout this subject wouldn’t have been much.

Marten Berglund

Uppsala, June 2011

Copyright©Marten Berglund and Global Energy Systems, Department of Physicsand Astronomy, Uppsala University.

UPTEC W11 021, ISSN 1401-5765

Printed at the Department of Earth Sciences, Geotryckeriet, Uppsala university,Uppsala, 2011.

v

Popularvetenskaplig sammanfattning

I den har rapporten behandlas fragan om det ar mojligt att leva i ett samhallemed standig ekonomisk tillvaxt1 utan att samtidigt tara pa naturresurser och miljopa ett ohallbart satt. Manga menar att det ar dagens konsumtionssamhalle somar grundorsaken till vara miljoproblem, och att vi ar tvungna att sla in pa enannan vag om vi ska kunna radda var planet fran utarmade resurser och okadetemperaturer.

En del menar a andra sidan att det ar den ekonomiska tillvaxten som gor att vihar rad att gora nagot at miljoproblemen, och som skapar mojlighet att utvecklanya energitekniker och renare industrier. En del statistik over landers ekonomiskautveckling och deras miljotillstand, visar till och med hur miljoproblemen i ett landvisserligen till att borja med forvarras med stigande BNP, men efter en viss nivatenderar dessa miljoproblem att avta ju hogre landets BNP blir. Detta samband,som kan beskrivas med en kurva som tar formen av ett uppochnedvant U, brukarkallas for miljo-Kuznetskurvan.

Detta resonemang gar dock att problematisera ytterligare. Uppstar denna miljo-Kuznetskurva aven nar man tar hansyn till den miljopaverkan som ett land orsakarutomlands genom sin import? Kanske ar det sa att var miljo pa hemmaplan harkunnat bli battre tack vare att vi har flyttat ut tung och smutsig industri tillandra lander som nu producerar de produkter vi efterfragar. Nar det galler fraganom huruvida var ekonomiska tillvaxt och var konsumtion ar hallbar eller ej, sakan det inte vara rimligt att bara titta pa den miljopaverkan som uppkommer iSverige, utan vi maste forstas ta reda pa vilka konsekvenser denna konsumtion farpa miljon i bade Sverige och utomlands.

I den har rapporten ar det just den svenska konsumtionens paverkan pa miljon ibade Sverige och utomlands som har analyserats. Ett centralt tema for rapportenar att de direkta miljoeffekterna som uppkommer av att ett foretag tillverkar enprodukt, inte ar det enda intressanta. For att tillverka nagot sa behover ju ettforetag kopa in andra produkter som har tillverkats nagon annanstans (eventuelltutomlands till och med), och dessa produkter har i sin tur sina bestandsdelar somtillverkats nagon annanstans, och sa vidare. Och i varje sadant steg uppkommermiljopaverkan. Att analysera denna tillverkningskedja ar sjalva poangen med denmetod som kallas for input–output-analys och som har anvants for att ta framresultaten i denna rapport.

Input–output-analysen ar fran borjan en ekonomisk metod, men nar den tillampasinom miljoomradet, sa ar den nara beslaktad med livscykelanalysen. Skillnadenar att nar livscykelanalysen tittar i detalj pa den miljopaverkan en viss speci-fik produkt orsakar genom hela sin livscykel, sa tittar input–output-analysen pamiljopaverkan fran en hel bransch, eller ett helt land.

1Med ekonomisk tillvaxt i ett land, menar vi okningen av det landets BNP, brutto-nationalprodukten.

vi

Pa satt och vis kan darfor denna rapport ses som en livscykelanalys over hela detsvenska samhallet. Det ar dock inte bara en livscykelanalys, utan for att kunna seutvecklingen over tid for de miljoeffekter som denna rapport tar upp, sa har up-prepade sadana har livscykelanalyser utforts for varje ar mellan 1993 till 2005. Demiljoeffekter som studerats ar anvandningen av fossila branslen (olja, kol och gas),samt utslappen av vaxthusgaser (koldioxid, metan och lustgas) och av svaveldiox-id, kvaveoxider, kolmonoxid och gruppen av fororeningar med sa kallade flyktigaorganiska amnen (exklusive metan).

Nar man forsoker ta reda pa t.ex. vilka utslapp som sker i Sverige eller utom-lands i de olika stegen i den har tillverkningskedjan som namndes tidigare, sa ardet – om man ska gora en analys over ett helt land – i stort sett omojligt attsamla in exakta uppgifter fran alla foretag om deras utslapp. Istallet baserar manberakningarna pa det ekonomiska vardet for de produkter som foretagen producer-ar, samt de totala utslappen for varje bransch. Pa sa satt far man fram en sa kalladutslappsintensitet, som beskriver ett for en viss bransch genomsnittligt varde pahur stora utslappen ar per krona producerad vara. Utslappsintensiteten ar sa attsaga kopplingen mellan de ekonomiska vardena i kronor, och de fysiska vardenai form av t.ex. kilo koldioxid. For att uppskatta de utslapp som var import or-sakar utomlands, anvands ocksa dessa utslappsintensiteter, fast justerat mot ettvarldsgenomsnitt pa grund av att Sverige har en mycket renare och mindre ut-slappsintensiv industri an vad som ar det normala i de lander som var importtillverkas i.

De mest intressanta resultaten i rapporten visar att gruppen av vaxthusgaser(koldioxid, lustgas och metan) har tillsammans ur ett konsumtionsperspektiv okatmed ca 20 procent mellan 1993 och 2005. Framforallt ar det metanet som bidragittill denna okning. Detta skiljer sig fran de officiella siffror som Sverige rapporterartill FN:s klimatkonvention, dar istallet en liten minskning har skett under sammaperiod. Okningen hanger direkt ihop med var okande konsumtion, i synnerheteftersom okad konsumtion ocksa innebar okad import och darmed okade utslapputomlands.

For samtliga luftfororeningar som ingick i studien galler vidare att de ligger pa enmycket hogre niva under hela perioden jamfort med de officiella siffrorna. Vissaresultat i studien ar dock mer positiva, t.ex. har utslappen av kolmonoxid underperioden minskat.

Slutsatsen som kan dras ar att for Sveriges del sa har den ekonomiska tillvaxten ansa lange inte kunnat forenas med minskande utslapp fran var konsumtion, atmin-stone inte i fallet med vaxthusgaser. Fler och noggrannare undersokningar behoverdock goras for att fa fram sakrare samband mellan tillvaxt och miljopaverkan,t.ex. genom att aven titta pa andra miljoproblem som ravaruanvandningen ochgenereringen av avfall.

vii

Contents

Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iii

Referat . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . iv

Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v

Popularvetenskaplig sammanfattning . . . . . . . . . . . . . . . . . . . . vi

Contents, List of Figures and List of Tables . . . . . . . . . . . . . . . . viii

1 Introduction 1

1.1 Objective of the study . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 Method, data and delimitations . . . . . . . . . . . . . . . . . . . . 2

1.3 Outline of the report . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.4 Supporting information and technical details . . . . . . . . . . . . . 4

2 Background 5

2.1 Analysing environmental problems . . . . . . . . . . . . . . . . . . 5

2.1.1 Ultimate versus proximate environmentalproblems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

2.1.2 The consumption versus the productionperspective . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

2.1.3 The IPAT equation . . . . . . . . . . . . . . . . . . . . . . . 9

2.1.4 The rebound effect . . . . . . . . . . . . . . . . . . . . . . . 10

2.1.5 The environmental Kuznets curve hypothesis . . . . . . . . . 11

2.1.6 Green growth and decoupling . . . . . . . . . . . . . . . . . 13

2.2 Stocks and flows in economic-ecological systems . . . . . . . . . . . 14

2.2.1 The mass balance of the society . . . . . . . . . . . . . . . . 14

2.2.2 The production–consumption “mass balance” . . . . . . . . . 15

2.3 Problems–solutions: concluding remarks . . . . . . . . . . . . . . . 17

2.3.1 Economic growth: Problem, solution or neither . . . . . . . 17

2.3.2 An overview of solutions . . . . . . . . . . . . . . . . . . . . 18

viii

3 Methodological framework 19

3.1 The national accounts . . . . . . . . . . . . . . . . . . . . . . . . . 19

3.1.1 The supply table . . . . . . . . . . . . . . . . . . . . . . . . 20

3.1.2 The use table . . . . . . . . . . . . . . . . . . . . . . . . . . 21

3.1.3 The input–output table . . . . . . . . . . . . . . . . . . . . . 22

3.2 The environmental accounts . . . . . . . . . . . . . . . . . . . . . . 25

3.2.1 Integrating national and environmental accounts . . . . . . . 26

3.2.2 Environmental data per industry and per product . . . . . . 27

3.3 Environmental input–output analysis . . . . . . . . . . . . . . . . . 28

3.3.1 Foundations of the input–output analysis . . . . . . . . . . . 28

3.3.2 Environmental extension to input–output analysis . . . . . . 34

3.3.3 Time series and EKCs based on input–output analysis . . . 36

3.3.4 Swedish studies . . . . . . . . . . . . . . . . . . . . . . . . . 39

3.3.5 Uncertainties . . . . . . . . . . . . . . . . . . . . . . . . . . 40

3.3.6 Other topics . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

4 Study-specific data and methods 42

4.1 Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 42

4.2 Economical data and methods . . . . . . . . . . . . . . . . . . . . . 43

4.2.1 Collection and pretreatment of economical data from SUTsand IOTs . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

4.2.2 Generation of IOT time series using updating methods foryears missing official IOTs . . . . . . . . . . . . . . . . . . . 44

4.2.3 Calculation of the Leontief inverse and the required produc-tion to meet final demand . . . . . . . . . . . . . . . . . . . 45

4.3 Environmental data and methods . . . . . . . . . . . . . . . . . . . 46

4.3.1 Collection of domestic environmental data . . . . . . . . . . 46

4.3.2 Calculation of domestic intensities . . . . . . . . . . . . . . . 48

4.3.3 Calculation of world average intensities . . . . . . . . . . . . 48

4.4 Master calculations . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

4.4.1 The master expression . . . . . . . . . . . . . . . . . . . . . 51

4.4.2 Physical trade balances . . . . . . . . . . . . . . . . . . . . . 52

4.4.3 Decomposition analysis . . . . . . . . . . . . . . . . . . . . . 52

4.4.4 IPAT and consumption–environmental impact relationships . 53

4.4.5 Product groups analysis . . . . . . . . . . . . . . . . . . . . 53

4.4.6 Analysis of final demand categories . . . . . . . . . . . . . . 53

ix

5 Results 54

5.1 Environmental impact from production in Sweden and abroad, andfrom direct use . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

5.2 Decomposition analysis . . . . . . . . . . . . . . . . . . . . . . . . . 59

5.3 IPAT diagrams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60

5.4 Consumption–environmental impact diagrams concerning decouplingand EKC patterns . . . . . . . . . . . . . . . . . . . . . . . . . . . 61

5.5 Environmental impact per product group . . . . . . . . . . . . . . . 62

5.6 Environmental impact per final demand category . . . . . . . . . . 64

6 Discussion and conclusions 65

6.1 Summary of main results and outcomes . . . . . . . . . . . . . . . . 66

6.2 Uncertainties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68

6.3 Comparison to other IOA and EKC studies . . . . . . . . . . . . . . 69

6.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70

6.5 Further research . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 72

Recommended readings 73

References 74

Appendices 91

Appendix A Glossary and abbreviations . . . . . . . . . . . . . . . . . . 92

Appendix B List of variables . . . . . . . . . . . . . . . . . . . . . . . . . 97

Appendix C Matrix algebraic conventions . . . . . . . . . . . . . . . . . 100

Appendix D Proof that An+1 converges to zero . . . . . . . . . . . . . . . 103

Appendix E SUT and IOT for Sweden 2005 . . . . . . . . . . . . . . . . 104

Appendix F Organization of the Excel database . . . . . . . . . . . . . . 105

Appendix G Excel tables . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

x

List of Figures

2.1 Cause–effect chain of environmental problems. . . . . . . . . . . . . 6

2.2 Environmental impact upstream and downstream the final con-sumption. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2.3 Global IPAT diagram for CO2, extended with the energy intensityof the world economy. . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.4 Schematic diagram of an environmental Kuznets curve. . . . . . . . 12

2.5 Simplified model of the societal mass balance. . . . . . . . . . . . . 15

2.6 Balance of supply and use – the production–consumption “massbalance”. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

3.1 The structure of economic and environmental data into one frame-work, a NAMEA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26

3.2 Binary tree describing production occurring domestically and abroadin the whole supply chain to satisfy final demand of domestic andimported products. . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

3.3 Plot of the surface e(v, i) = vi. . . . . . . . . . . . . . . . . . . . . . 38

5.1 Consumption-based time series of oil use, coal use, gas use, andfossil fuel use. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

5.2 Consumption-based time series of greenhouse gas emissions. . . . . 56

5.3 Consumption-based time series of SO2, NOx, CO and NMVOCemissions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57

5.4 Decomposition analysis of change in oil use, and in CO2, CH4 andSO2 emissions, in the period 2000–2005. . . . . . . . . . . . . . . . 59

5.5 Consumption-based IPAT diagrams for fossil fuel use, and for CO2,CH4 and SO2 emissions in the period 2000–2005. . . . . . . . . . . . 60

5.6 Consumption-based environmental impact versus domestic final de-mand for fossil fuel use, and for CO2, CH4 and SO2 emissions. . . . 61

5.7 Fossil fuel use and emissions of CO2 equivalents in 2000–2005, forgoods and for services less transports in the production-based caseand in the consumption-based case. . . . . . . . . . . . . . . . . . . 62

xi

5.8 Consumption-based emissions of CO2 equivalents in 1993–2005, dis-tributed over the various categories of final demand. . . . . . . . . . 64

F.1 Relations between the files in the Excel database. . . . . . . . . . . 105

xii

List of Tables

5.1 Consumption-based and production-based data, and physical tradebalance, for fossil fuel use and CO2 equivalents. . . . . . . . . . . . 58

5.2 Consumption-based and production-based emissions of CO2 equiv-alents, per various product groups. . . . . . . . . . . . . . . . . . . 63

xiii

Chapter 1

Introduction

The consumption society and the economic system of today’s world with its urgefor continuous economic growth, has among many environmentalists and concernedcitizens been pointed out as being the root cause to all environmental problems.

This is however not a trivial and undisputed fact since – as many economists hasargued – when looking at various countries in the world, the richer the country, theless environmental problems the country has, at least to some extent. This relationis described by the so called environmental Kuznets curve: as a country developsit goes through a stage of deteriorating environment, which, after a sufficient levelof development, starts to level off and eventually the environment in the countrystarts to improve.

However, such conclusions are based on measuring the environmental load onlyin that particular country. Going one step further, it is therefore reasonable toanalyse that particular country’s environmental pressure on the world as a whole,and find out if that load is increasing or decreasing with increasing prosperity.Only then could we more accurately determine if the consumption society of today– and in particular the economic growth – is associated with the environmentalproblems or not.

This study is an attempt to contribute to that project, by analysing the envi-ronmental pressure Sweden and its citizens impose on the world, and how thatpressure is developing with time and economic level.

The most widely used method to examine the environmental effects of the con-sumption for a whole country, is environmental input–output analysis.1 Input–output analysis is a powerful method used in economics to analyse the productionneeded upstream throughout the whole supply chain, to satisfy the consumptionof some product or, collectively, some set of products. The environmental input–output analysis extends this to cover all the environmental pressure, e.g. emissions,occurring upstream throughout the whole supply chain, caused by some kind ofconsumption – including the emissions occurring abroad. It can be considered tobe a sort of life cycle assessment, applicable to whole industries or whole countries.

1See Chapter 3.3 for studies.

1

2 Introduction Chapter 1

This study can in that sense be regarded as a time series of life cycle assessmentsof Sweden as a whole country.2

1.1 Objective of the study

The primary objective of the study is to evaluate whether the environmental pres-sure that the Swedish consumption causes is increasing or decreasing with timeand economic level. A secondary objective, motivated by climate change nego-tiations, is to examine the official figures of environmental pressure such as CO2

that are allocated to Sweden compared to the environmental pressure Swedishconsumption causes. Another secondary objective is to estimate the environmen-tal pressure caused by consumption of different kinds of products, in order to seewhich type of consumption should be encouraged or discouraged.

1.2 Method, data and delimitations

To determine the environmental pressure caused upstream by Swedish consump-tion, an environmental input–output model of the Swedish economy is developed.The model developed is a single-regional input–output model, augmented withworld average energy and emission intensities for the production occurring abroad.This means that the model, in theory, includes all emissions from the whole sup-ply chain from the whole world, but with some assumptions, the most importantbeing that the production structure for the world is approximated by the Swedishproduction structure, and that all emissions abroad have the same intensities, nomatter where abroad they are produced.3 When speaking about Swedish consump-tion here, we mean, in economic terminology, final demand less exports, i.e. publicand private consumption, and investments, but not exports (however, investmentsin the exports industry have not been excluded).

The environmental pressure caused downstream after consumption, i.e. the pres-sure caused by use and disposal, is also part of the study.

Economic data come from the Swedish national accounts in two revisions, one forthe period 1993–2003, the other for the period 2000–2005. Environmental datacome from a newly revised time series from the Swedish environmental accountscovering 1993–2005; all environmental variables in the environmental accountsthat refer to fossil fuels are used; all environmental variables in the environmentalaccounts that have its correspondence in the official UNFCCC emissions data havebeen used. Environmental data for the world are taken from recently publishedfigures from the IEA, and from the international EDGAR emissions database, both

2This analogy is used by e.g. Hendrickson et al., 2006.3World average intensities for the rest of the world could be accused for being quite a strong

assumption, but in Chapter 4.3.3 it will be concluded that it is reasonable.

Chapter 1 Introduction 3

covering the period 1993–2005. World economic data to calculate world averageintensities, come from the World Bank.

The environmental variables are the following:

� Fossil fuels: Oil, coal and gas use, and the aggregate fossil fuel use. Notethat this is fossil fuel use, and not supply, i.e. transformation losses are notincluded.

� Emissions: CO2, CH4, N2O, SO2, NOx, CO and NMVOC, and the aggregateCO2 equivalents.

Environmental variables are plotted against time and against economic level. Eco-nomic level is final demand less exports per capita.

The purpose with the broad selection of environmental variables has been to givean overview only of the consumption-based development of these variables, en-couraging more in-depth analysis of specific variables for future studies. Environ-mental variables not part of the study are for instance use of minerals, water use,overfishing, total oil consumption (only oil used for fuel is counted in this study,e.g. oil in plastics industry is not included), total energy consumption (includingconsumption of electricity), emissions of phosphorus and nitrogen to aquatic sys-tems, emissions of persistent organic pollutants, and waste flows. Also, changes inemissions due to natural sinks like land use change and forestry, are not included.Environmental pressure, like emissions caused by the treatment of waste exportedto other countries, is not included either. Another issue not included is the de-velopment of the Swedish ecological footprint, which would be a relevant issue toanalyse in future research. See Chapter 6.4 for an overview of aspects not part ofthis study but which are suggested for further research.

1.3 Outline of the report

After this introduction, a background follows in Chapter 2 that dwells more deeplyinto the rationale and context of the study, analysing in more detail the debateabout economic growth and environmental degradation. Chapter 3, gives thetheoretical foundation of the environmental input–output analysis, as well as itsfoundation in the system of national accounts, and the environmental accounts.Chapter 4 describes in detail the method used in this study and Chapter 5 presentsthe results. In Chapter 6 the results and conclusions drawn from them are dis-cussed, and an overview of the various outcomes of the whole study is presented;this chapter also concludes with suggestions for further research.

4 Introduction Chapter 1

1.4 Supporting information and technical details

Homepage of the report : Supporting information, i.e. the whole Excel databasewith all calculations and results, can be found on the following web page:http://www.fysast.uu.se/ges/en/marten-berglund.

Email of the author : The author of the report can be contacted through e-mail [email protected].

Browsing the report : It is possible to browse the PDF version of the report as ahypertext. Headings in the table of contents, literature references in footnotes andchapter references etc. are all clickable links. After clicking, to return to where youwere, push Alt + left arrow. To go forwards again, push Alt + right arrow. Thesame applies to the blue links in the contents sheets of the Excel database. Manyof the references in the reference list also have links attached which by clickingleads directly to the referred text on the Web (some texts may require subscriptionthough).

Software: The report is written in LATEX with the help of the LYX editor. Figuresare drawn in Inkscape, and diagrams are made in MATLAB. The database is builtin Microsoft Office Excel.

http://www.fysast.uu.se/ges/en/marten-berglund

mailto:[email protected]

Chapter 2

Background

2.1 Analysing environmental problems

2.1.1 Ultimate versus proximate environmentalproblems

This master thesis has its origin in the quest for the ultimate environmental prob-lem, and its corresponding solution. Talking about the ultimate environmentalproblem in this context, doesn’t mean to assess which of the global environmentalproblems – whether it is climate change, oil depletion, water scarcity or overfish-ing, to name but a few – that is the most important environmental problem, butto find the ultimate causes behind these problems.1 It is a question about to re-alize where the true problem causing all other environmental problems really lies,which, if solved, has the most power to solve all the actual environmental problemsmankind faces.

This suggests that environmental problems exists at various levels. Suppose wehave a sea with dead fish. Some would say the high concentration of aluminumions in the sea is the environmental problem, others would say it is the sulfurdeposition onto the sea that is the environmental problem, still others would sayit is the industries and the transports producing the sulfur dioxide that is theenvironmental problem. All are in a sense right. The former are pointing toproximate environmental problems, the latter to ultimate environmental problems.Proximate problems have their corresponding proximate solutions (lake liming),ultimate problems their ultimate solutions (flue gas treatment, regulations). Inthis way environmental problems and their solutions can be organized into anultimate–proximate spectrum.2

1The terms ultimate and proximate are here used in a new way, corresponding to a similarusage in biology, sociology and philosophy. See e.g. Campbell, 1996, and Mayr, 1961.

2See Meadows, 1999, for an excellent account of how to deal with environmental problems ina similar way, finding the solutions that has the most power to impose change. Daly and Farley,2004, uses a similar approach, using an ends-means spectrum.

5

6 Background Chapter 2

The ultimate–proximate spectrum of environmental problems should in this con-text be interpreted as a cause–effect chain. Environmental problems on lower levelshave their causes on higher levels, and trying to solve an environmental problemthrough taking care of the direct proximate causes of the problem on a lower level,often mean to engage in suboptimization, leading to the problem disappearingin one place or appearance, popping up in an other place or appearance. Thiswould be the case when there are other more ultimate causes, which will continueto create new environmental problems if not these ultimate causes are addressed.Thus, taking care of the proximate causes are often in vain – instead, solvingenvironmental problems must be done upstream in the cause–effect chain.3

Looking into Figure 2.1 gives an illustration with examples from the area of climatechange.4 Going to the left in the figure, the ultimate causes of the environmentalproblem and its corresponding ultimate solutions are shown. Going to the right,the proximate causes of the environmental problem and its corresponding prox-imate solutions are shown. For instance, when the effects of climate change areinevitable, geoengineering or finally adaptation might be the only remaining mea-sures available. More preferably would be to limit the withdrawal of fossil fuels, orultimately, to reform the world economy, in order to prevent the effects of climatechange to arise in the first place.

Even though the needs of society should be interpreted as an ultimate cause left-most in the figure, they are at the same time a part of the society, shown as thedotted round figure inside the anthroposphere box. The needs of society5 are therethe main factor pulling products from the supply chain upstream, shown by thethree arrows to the left inside the anthroposphere box.6 The rightmost arrow inthe anthroposphere box, denotes downstream effects after consumption, i.e. usage

AnthroposphereNature

NatureNeeds of societyx efficiency

Environmental problem:

Examples:

Solution:

Economic growth?

The world economy

Green GDP?Performance economy?Steady-state economics?

Resource depletion

Peak oil

Limit withdrawalUse recycled materials

Emissions, waste

Burning of fossil fuels

Treatment, recycling

Contamination

CO2eq > 450 ppm

Geoengineering

Impact on society

Risen sea levels

Adaptation

LithosphereHydrosphere

Etc.

Figure 2.1. Cause–effect chain of environmental problems.

3Robert, 2000, talks about upstream thinking in cause–effect chains.4Though not exactly the same, Graedel and Allenby, 2010, use a similar approach for envi-

ronmental problems in general.5In economic terms this corresponds to the so called final demand, i.e. consumption in a

general meaning.6Though the final demand is the driving factor in this model, it should not be concluded that

the consumers are the sole responsible. As e.g. Sanne, 2007, argues, the industry is in a greatdeal responsible for pushing consumers to buy their products. But yet, this is again ultimatelydriven by the eager to grow economically.

Chapter 2 Background 7

and disposal. All arrows denote a cause–effect relation, thick solid arrows denotea material flow as well.

Accordingly, many researchers have suggested that the current economic systemwith its demand for continuous economic growth may be the ultimate cause to allother environmental problems.7 Meadows goes even further upstream in the cause–effect chain talking about the current paradigm of thinking, and to reconsider whatreally matters in our lives.8

This leads us to the core of this study, which goes no further than to the level of theeconomic system. Its aim is to contribute to that project which tries to determinewhether the economic system is the ultimate (so far) environmental problem ornot. If it is concluded that the economic system is the ultimate environmentalproblem, other studies need to develop ultimate solutions to that problem. If,on the other hand, it is concluded that the economic system is not the ultimateenvironmental problem, we need to study other parts of the cause–effect chain.9

This is important, since we must first try to obtain an accurate description of whatis really the problem, before trying to find solutions.10

2.1.2 The consumption versus the productionperspective

When we talk about the needs of society and the effects these needs cause, it isimportant that we take into consideration not only the direct effects these needscause when producing the products needed, or the effects caused in just one par-ticular country (like the effects on the Swedish territory), but also all the upstreameffects caused throughout the supply chain.11

This can be understood by looking at Figure 2.2, which as an example shows theemissions of CO2. The needs of society, e.g. the needs of the Swedish consumers(i.e. exclusive consumption abroad through exports) are there represented by thefinal consumption. The final consumption should be interpreted as a vector ofvarious product groups consumed by ordinary people – an element in that vectorcould for instance be cars purchased and used for private purposes and not for usein the industry.

When a product is consumed at the final consumption stage, it has to be producedin the stage just before that, leading to emissions in that stage. But for that

7Meadows et al., 1972, Jackson, 2009, and Rockstrom and Wijkman, 2011, to name but afew. In works of Hornborg, theories from thermodynamics are used to argue for the society–biosphere system being a zero-sum game, and that technological development is in vain; see e.g.Hornborg, 1992, and Hornborg, 2010.

8Meadows, 1999.9For instance Radetzki, 2010, Goklany, 2007, and Beckerman, 1992, propose that economic

growth is an essential contributor to the solution of environmental problems.10This, and some of the reasoning in the preceding paragraphs, is also discussed in Ariansen,

1993.11E.g. Spangenberg and Lorek, 2002.


Anthroposphere

CO2CO2 CO2 CO2 CO2 CO2

Supply chainFinal

consumptionvector

Usage Disposal

Figure 2.2. Environmental impact upstream and downstream the final consumption.

product to be produced, the producer needs to consume other products (throughso called intermediate consumption, in contrast to final consumption) from theproduction stage just before that. And the products in that stage need in turnother products from the stage before that, and so on, all the way through the wholesupply chain (the three dots leftmost in the figure indicates that this supply chaincan be infinitely long). The total emissions occurring throughout the whole supplychain correspond to the emissions in the consumption perspective.12 Calculatingall the emissions occurring in the whole supply chain is done with the help ofinput–output analysis, which is the main method employed in this study.

For clarity in Figure 2.2, arrows indicating imports have not been drawn but shouldbe considered implicit. That means that all arrows in the supply chain includesimports, and thus imports are included in the consumption perspective.

In Figure 2.2, the downstream effects are also shown. That is the effects occurringafter the final consumption stage, i.e. effects during usage and disposal.13 Inlife cycle assessments, upstream effects correspond to the production phase anddownstream effects to the use and disposal phase, though in such studies only aspecific product is analysed, and just a few steps of the supply chain are included.In this study all upstream and downstream effects are included for all productsconsumed by Swedish consumers.

In Figure 2.2, it is also possible to see the emissions occurring from a productionperspective, i.e. emissions occurring in all phases shown in the figure, but only onthe domestic territory, and no matter if domestic consumers or consumers abroad(exports) caused the emissions. Looking into the reporting done in Sweden, moststatistics and analyses use a production perspective. That is for instance the casewhen it comes to the sixteen environmental quality objectives, which the Swedishparliament has agreed upon.14

In this study we will focus on the consumption perspective, including downstreameffects, in order to determine all environmental impact caused by Swedish citizens.

12See e.g. Peters and Solli, 2010, Davis and Caldeira, 2010, Swedish EPA, 2010a, Wiedmann,2009, Peters, 2008, Peters and Hertwich, 2008, and Rothman, 1998.

13OECD, 2001, uses downstream in this way.14Though, in one of its latest report from the Environmental Objectives Council, the con-

sumption perspective is briefly analysed for the first time – see Swedish EPA, 2010a. For furtherSwedish analyses using a consumption perspective, see Chapter 3.3.4.


2.1.3 The IPAT equation

As we have suggested above, it is the needs of the society – i.e. the consumption –that is to some extent the ultimate cause and the factor driving the environmentalproblems. Leftmost in Figure 2.1 this is expressed as the needs of society timesthe efficiency to fulfil these needs.

Let us examine this in more detail. To be more precise, the needs of the societycould be said to be equal to the number of humans, times the need per human,times the efficiency by which the society fulfil these needs. This is exactly whatthe so called IPAT equation says,

(2.1) I = P × A× T

which states that the environmental impact (I) equals the size of the popula-tion (P ) times the affluence (A) of the population times a technology factor (T )denoting the efficiency by which that affluence is generated.15

Affluence is normally referring to GDP per capita or income per capita,16 butwe will according to what has been said before focus on the need per capita,expressed as the consumption per capita.17 The technology factor, expressed asenvironmental impact per unit of GDP, e.g. CO2 per GDP, will consequently beinterpreted as CO2 per unit of consumption. To refer to the technology factoras the efficiency factor is strictly speaking incorrect, since it rather measures theinefficiency. Further on we will refer to this factor as the intensity of the productionor the consumption, i.e. how much resources needed or emissions emitted for theproduction or consumption of one unit.

Sometimes the intensity factor T , is further decomposed into an energy intensityfactor Te (joule per GDP) and a carbon intensity factor Tc (CO2 per joule):18

(2.2) I = P × A× Te × Tc ,

or in the case of CO2

(2.3) CO2 = Population×GDP/cap× J/GDP × CO2/J .

Thus, we now have a way to analyse various factors driving the environmentalimpact.

In Figure 2.3, an extended IPAT equation (corresponding to equation (2.2) and(2.3)) for the whole world is shown. There one can see that population growth andeconomic growth have been the driving factors, while the energy intensity of the

15The IPAT equation came up during an environmental debate in the beginning of the 1970s,see e.g. Ehrlich and Holdren, 1970 and 1971, and Commoner, 1972. For a critical analysis, seeDietz and Rosa, 1994.

16Income per capita, also expressed as GDI per capita, is approximately the same as GDPper capita – see Sandelin, 2005.

17This was also what Ehrlich and Holdren, 1970, used.18This is then called the Kaya identity, see Davis and Caldeira, 2010.


1970 1980 1990 2000 20100

20

40

60

80

100

120

140

160

180

200

J/GDP

Year

Global IPAT for CO2, 1971-2007

Inde

x (1

971

= 10

0)

Population

CO2CO2/JGDP/cap

Figure 2.3. Global IPAT diagram for CO2, extended with the energy intensity of theworld economy. GDP are in constant 2000 US dollars. Source: Data from the WorldBank, 2010.

world economy has had a restraining impact, though not even close to the degreepopulation and economic growth have been increasing. Even though populationgrowth is expected to decline and only grow an approximate 60 percentage pointsthe coming 40 years,19 if GDP/capita is growing linearly at the same rate as thelatest 40 years (approximately 80 percentage points the coming 40 years), and ifenergy efficiency doesn’t improve faster than it has done the latest 40 years, theprospects for decreasing CO2 emissions in the near future look not so encouraging.However, the assumption that the variables in the IPAT equation are linear maynot be realistic, and the future development may be much more uncertain.20 Butanyway, what is crucial here is if it possible to decrease the T factors at a fasterrate than the P and A factors increase.

2.1.4 The rebound effect

Accordingly, looking at Figure 2.3 reveals that as the energy intensity of the worldeconomy has declined, GDP/capita has increased still more, which consequentlyhas lead to continued increasing CO2 emissions. This may lead us to the conclu-sion that efficiency improvements always entail improved turnovers and therebyincreased environmental pressure. This is the hypothesis behind the rebound effect– every efficiency improvement will lead to higher volumes, eating up some of thereduced resource demand that the efficiency improvements to begin with resultedin, or sometimes even has as a consequence that the total resources needed will in

19UN, 2011.20E.g. Victor, 2008, points out that the factors in IPAT depend on each other, and that the

impact is dependent also on the composition of the GDP.


fact increase.21,22 Even though the rebound effect may not arise as a logical conse-quence of improved efficiency, awareness of its existence among policy makers andin industry is crucial if the absolute environmental pressure are to be decreased.23

The rebound effect can be direct or indirect.24 Direct effects are increased con-sumption of a product, due to the decreased energy intensity of that product.Indirect effects happen when increased efficiency leads to lower prices and in turnmore space for consuming other products.

An important limitation of many environmental systems analysis tools like the lifecycle assessment methodology or environmental management systems,25 is thatthey focus mainly on the environmental impact per unit of product, and tendsto disregard the volume effect.26 Similar conclusions are drawn in a couple ofstudies by Alfredsson27 where the positive effect of “green consumption” is shownto be eaten up by the growth in income. Consequently, looking at the IPATequation and considering the rebound effect, is utterly important when evaluatingenvironmental performance.

2.1.5 The environmental Kuznets curve hypothesis

Now, let’s turn our attention to the I and A factors in the IPAT equation. Thatis, let’s look at how the environmental impact relates to the growth in the GDPper capita. It turns out that for many pollutants in the richer world, the relation-ship has an inverted u-shaped form: as the country develops the environmentaldegradation in that country increases until a certain point when the environmen-tal degradation starts to decrease. This is the hypothesis of the environmentalKuznets curve (EKC).

The name origins from the economist Kuznets, who in the 1950s wrote a papersuggesting that as a country develops it goes through a stage of increasing incomeinequality which after a sufficient level of development is reached, turns to anincreasing income equality.28 In the environmental analogy to this Kuznets curve,environmental degradation is substituted for income inequality.

In Figure 2.4 a schematic diagram of an EKC is shown. The y axis normally refersto environmental degradation inside the particular country of study, and the x

21Also known as the Jevons paradox from the 19th century British economist William StanleyJevons, or the Khazzoom-Brookes postulate See Herring and Sorrell, 2009. See Jevons, 1866, forthe original work.

22Tsao et al., 2010, attracted much attention by asserting that when LED lamps become moreprevailing in society, total energy demand probably will increase.

23See von Weizsacker et al., 2009, and Herring and Sorrell, 2009, for suggestions of how toprevent the rebound effect.

24Swedish EPA, 2006, and Herring and Sorrell, 2009.25See Finnveden and Moberg, 2005 for a good overview of environmental systems analysis

tools. An attempt to organize various environmental systems analysis tools is also done in TheNatural Step framework presented in Robert, 2000, and Robert et al., 2002.

26See Axelsson and Marcus, 2008, regarding environmental management systems.27Alfredsson, 2002 and 2004.28Kuznets, 1955.


Environmental degradation

Economic level

Figure 2.4. Schematic diagram of an environmental Kuznets curve.

axis to the GDP per capita or income per capita. However, in this study we willcontrast this with the environmental degradation all over the world caused by theconsumption in a particular country, plotted against consumption per capita (ormore precisely, against domestic final demand per capita).

Statistical studies like the ones used for testing the hypothesis of the EKC, comein two different shapes: cross-sectional studies and longitudinal studies.29 In thecontext of EKCs, cross-sectional studies, are most often cross-country studies,i.e. these studies plot these countries’ environmental performance against thesecountries’ GDP/capita. However, in some cross-sectional EKC studies, analysis isperformed with consumption groups divided by level of income, in order to deter-mine how the environmental impact varies with level of income.30 Longitudinalstudies on the other hand, analyse time series data of environmental performancefor a given country or region; this is the kind of study that has been performedfor this report.

The first studies of EKCs came in the beginning of the 1990s and analysed bothvarious emissions and natural resource uses as functions of income per capita.31

The results were that most emissions and resource uses actually declined withlevel of income per capita, except for waste generation and CO2. Although mixedresults have been dominating the EKC studies, the general picture is that localpollutants tend to follow an EKC pattern, while global environmental problemslike CO2 emissions tend to have an ever increasing trend with income per capita.The Swedish situation looks similar,32 though in Sweden there is some support forCO2 also declining, with a longitudinal study by Kander even showing a typicalEKC pattern.33 However, important to remember, these studies don’t considerthe environmental degradation caused abroad by the domestic consumption.

The mechanisms explaining the EKC pattern could be of three sorts.34 Firstly,as an economy grows beyond a certain stage, the demand for more service ori-ented products begins to dominate. Secondly, wealthier countries can afford to

29Compare Andersson et al., 2007.30E.g. Roca and Serrano, 2007.31See Grossman and Krueger, 1991, and Shafik and Bandyopadhyay, 1992. For a comprehen-

sive survey up to 1997, see Kageson, 1997. For a recent literature survey, see Carson, 2010.32See for instance Johansson and Kristrom, 2007 for SO2.33Kander, 2002, and Kander and Lindmark, 2006.34Adopted from Galeotti, 2003.


spend more money on cleaner technologies and more efficient ones. Thirdly, as theaverage income of the individuals in a country increases, they become more envi-ronmentally aware, and the country as a whole starts to introduce environmentallegislation and environmental policies.

Another factor explaining the EKC pattern – which is also one of the main cri-tiques that has been delivered – is the possibility that environmental performancehas been improved due to the fact that products from more heavy and dirty in-dustries are being imported from abroad.35 In the literature, this is sometimescovered under the term the pollution haven hypothesis or carbon leakage.36 We-ber and Peters conclude that although there is little support for industries movingto countries with less strict environmental legislation, due to stricter environmen-tal policies at home, several studies suggest parts of the increasing consumptionis met by production abroad, consequently leading to higher emissions generatedabroad.37

This takes us back to what was concluded in Chapter 2.1.2 regarding the con-sumption versus the production perspective. If the purpose is to determine if oureconomy has been able to grow without any negative consequences on the envi-ronment, we must take into account all the environmental impact caused by theeconomy, or caused by the consumption of our economy, within and outside ourborders. Accordingly, diagrams showing the relationship between environmentalimpact and GDP or consumption, must show the consumption-based environmen-tal impact for being meaningful.38 Thus, in this study, the purpose is to generateconsumption-based such diagrams.

2.1.6 Green growth and decoupling

In this context, the concept of green growth and decoupling is fundamental, thatis when the growth in GDP or income is decoupled from the growth in naturalresource use or the growth in emissions.39 Decoupling could be relative or abso-lute.40 Relative decoupling means that the emission intensity of an economy is notanymore rising with rising income. For the world economy this has already hap-pened with the energy intensity, as was shown in Figure 2.3. Though this measurecould be interesting in some types of analyses,41 as, again, Figure 2.3 showed, theoverall emissions were still on the rise. Therefore, absolute decoupling is in this

35See for instance Arrow et al., 1995, Stern et al., 1996, and Rothman, 1998.36See Fullerton, 2006, and Weber and Peters, 2009. Carbon leakage is the carbon leaking

from e.g. Annex B countries to non-Annex B countries, due to undertakings the country hassigned under the Kyoto protocol.

37This is sometimes referred to as “weak carbon leakage” or demand-driven displacement, incontrast to “strong carbon leakage” or policy-induced displacement. See Peters and Solli, 2010,and Weber and Peters, 2009.

38This was the main conclusion in Rothman, 1998, and also commented in the EKC surveyby Carson, 2010.

39Victor, 2010, The Natural Edge Project, 2008, Azar et al., 2002, and OECD, 2002.40OECD, 2002.41E.g. Kander, 2002, focuses on relative measures.


context a more relevant measure, i.e. a situation when the economy grows at thesame time as the emissions are constant or decreasing.42

However, absolute decoupling is not good enough. Obviously, if CO2 emissionscontinue to be high, while neither increasing or decreasing, this is not enough aswe need to lower our CO2 emissions. This reasoning can go even further, sayingthat not even when the emissions are decreasing it is good enough, because weare still increasing the accumulated levels of CO2 in the atmosphere as long asthe emissions are higher than the natural sustainable uptake in the biosphere,even though we’re then on the right track. Not before the emissions actually arenegative, we’re coming somewhere.

2.2 Stocks and flows in economic-ecological sys-

tems

2.2.1 The mass balance of the society

When we have been talking about environmental degradation in the precedingsections, we have been a little bit unclear of what exactly we are referring to. Dowe refer to the level of how much the environment in total have been degraded, i.e.the level of remaining resources in a resource pool and the level of accumulatedpollutants in the biosphere, in other words, the stocks? Or do we refer to theongoing process of environmental degradation, i.e. the flows of extracted resourcesand the flows of emitted pollutants?43

It is important to distinguish between these two – the stocks and the flows – aswas shown in the section above about decoupling: it is not good enough to reacha constant level of CO2 flow into the atmosphere, since integrating this flow overtime, yields an increasing stock of carbon content in the atmosphere. A similarreasoning is essential in the debate on oil depletion and peak oil: peak oil is notabout the oil resources running out, but about how and when the flow of oil fromthese resources will reach its maximum.44

Consequently, analysing only the flows gives us an incomplete picture. However,measuring the level of the stocks could have its complications, since e.g. laggingmechanisms in natural systems like buffering, will make it hard to see the truelevels. Therefore, most EKC studies analyse flows, but there are exceptions, asone of the first EKC studies also analysed the total accumulated deforestation.45

In our study, only the flows are studied.46

42This is also emphasized in Azar et al., 2002.43This conceptual model is described in many places, like Graedel and Allenby, 2010, and

Daly and Farley, 2004. In Kageson, 1997, these concepts can be considered included in thepressure–state–response model presented there.

44Aleklett and Campbell, 2003.45Shafik and Bandyopadhyay, 1992.46The distinction between stocks and flows in EKC studies is also made in Carson, 2010.


To get a more comprehensive picture of the stocks and flows between the society –the anthroposphere – and the nature, we will elaborate Figure 2.1 a bit, focusingon the anthroposphere box and its closest interactions – see Figure 2.5.47 In thisfigure, the levels of the resource stocks, like oil and fossil water, are shown tothe left. These resource stocks decrease as they flow into the anthroposphere.If not accumulated in the anthroposphere, they transform and flow out of theanthroposphere as emissions or waste, eventually increasing the levels of variousstocks in nature to the right in the figure, like the carbon stock in the atmosphere.

The mass balance of the society in the figure can be expressed as

(2.4) R =dA

dt+ E ,

where R means the resource use inflow, dAdt

the rate of change of mass in theanthroposphere, and E is the outflow of emissions.48 Accordingly, as can be notedby Figure 2.5 and equation (2.4), environmental problems can be divided into twogroups, depending on if they belong to the inflow side, or the outflow side.

Anthroposphere

Oil

Water

Minerals

Fishstocks

CO2 stockin atm.

SO2

PCB

Waste

Figure 2.5. Simplified model of the societal mass balance.

2.2.2 The production–consumption “mass balance”

Stocks and flows are also fundamental in economics,49 and a “mass balance” of theeconomy can be expressed in a similar way, which fits into the overall mass balanceshown in Figure 2.5. We’re now referring to a balance between production andconsumption, or to be more precise, between the value of the supply of products,and the value of the use of products.

Looking into Figure 2.5, and recalling the interpretation of the arrows inside theanthroposphere box, the three arrows to the left in that box represent the produc-tion side, and the small dotted circle the consumption side (the rightmost arrowis disregarded for the moment). If the production side is to include productionfrom abroad as well, i.e. the imports, and the consumption side is to include the

47A model like this one is one of the main components in the field of industrial ecology, wherethe “metabolism” of the society is studied. See e.g. Graedel and Allenby, 2010. A similar figureis also presented in Statistics Sweden, 2002a.

48See Graedel and Allenby, 2010, for a similar version. This is ultimately based on the law ofconservation of mass.

49UN et al., 1993.


investments made, and the foreign consumption abroad of domestic products, i.e.the exports, the following supply–use balance can be put forward:50

(2.5) GDP + Imports = Consumption + Gross investments + Exports .

The production–consumption “mass balance” equation corresponding to equation(2.4) then becomes

(2.6) GDP + I =dS

dt+ D + C + E ,

where GDP here should be interpreted as the production flow, I is the flow ofimports, dS

dtis net investments, i.e. the rate of net change in the capital stock, D

is the depreciation flow, i.e. the decrease in the existing capital stock, C is theconsumption flow, and E is the flow of exports.

This balance can now be concluded in a similar figure like Figure 2.5 – see Fig-ure 2.6. Note though, that here, in the use of supplies going to gross investments,it is only the depreciation part that is an outflow – the rest (net investments) isaccumulated in the capital stock. This is depicted in the figure by the small arrowsinside the capital stock box, showing that gross investments can be divided into adepreciation part and a net investments part. I.e. an initial decrease in the capitalstock through depreciation, will possibly turn into a net increase in the capitalstock when the gross investments been added.

Even though this is a balance of values, and not of masses, its resemblance tothe societal mass balance will be of interest in this study. Further on, value flowsand stocks are often the only proxies available for determining the mass flows andstocks, since data on economic values are much more readily available. To convertvalues to masses, intensities are the fundamental tool applied, e.g. CO2 emittedper dollar’s worth of produced products.

It is important to note in Figure 2.6, that GDP is a flow, and is not equal to thewealth of the society, here corresponding to the capital stock. Increasing GDP,i.e. economic growth, doesn’t mean to increase the wealth of the society. In fact,

Anthroposphere

Capital stock

Grossinvestments Depreciation

Net investmentsGDPImports

DepreciationConsumptionExports

Figure 2.6. Balance of supply and use – the production–consumption “mass balance”.

50See e.g. Eklund, 2004. Statistics Sweden calls this the balance of resources, a term not usedin the international terminology though – Statistics Sweden, 2011a.


it could very well involve the decreased value of the wealth through depreciation(value destroyed), since GDP includes gross investments, which in turn includedepreciation. Furthermore, the wealth of the society is not only the economiccapital stock depicted in Figure 2.6, but also the natural capital stock resources,as depicted in Figure 2.5. In this sense, a sustainable society is a society wherethese boxes in Figure 2.5 and 2.6 are not decreasing. The concept of a green GDPcomprehends these aspects, and will be discussed further on in this report.

2.3 Problems–solutions: concluding remarks

2.3.1 Economic growth: Problem, solution or neither

We began this chapter by discussing ultimate and proximate environmental prob-lems, asking ourselves if economic growth and the growth in consumption is anultimate cause to most other environmental problems. This study belongs to thatgrand project which tries to find answers to that central question. When the re-sults of that project begin to crystallize, other projects follow concentrating onthe solutions to the problems the former project has pointed out. In that sense,this study belongs to the problem formulation side of the environmental problems–solutions dichotomy.

Here it is of interest to structure the various possible outcomes of this research alittle bit. What we have seems to be three possibilities:

1. Economic growth causes the environmental problems. Stopping economicgrowth is the solution.

2. Economic growth doesn’t cause the environmental problems. However, eco-nomic growth does neither solve the environmental problems.

3. Economic growth solves the environmental problems.

However, finding clear and concise causal relationships like these, could be a del-icate task. Just because B happens after A, doesn’t mean that B happens as anecessary consequence of A. Something else, C, may have happened at the sametime without our notice, which really caused B to happen.51 In other words,correlation does not in itself imply causation.52

Moreover, if we refer to the IPAT equation, growth may result in better technology(decreased intensity and thus a decreased T factor), but may at the same timeincrease the scale even more (an increased A factor). Consequently, growth couldbe the cause behind increased environmental impact, and at the same time causing

51Compare Hume, 1739.52However, it is possible to analyse causal relationships like these using e.g. Granger causality.

See Granger, 1969, and for applications regarding economic growth versus energy use, see e.g.Cleveland et al., 2000, and Ozturk, 2010.


this impact to be not as high. In other words, growth could simultaneously bothcause and solve the environmental problems – a combination of point one andthree above.

The degree to which growth contributes in decreasing intensity will not be analysedin this study. Here we will only try to determine whether or not economic growth– in particular growth in domestic final demand – has been a driving force inincreasing environmental impact. This will be done by a simplified decompositionanalysis.53

2.3.2 An overview of solutions

To sum up this chapter, we will still give a brief overview of the solution side of theenvironmental problems–solutions dichotomy, solutions discussed in the literatureand the public debate. In this context, solutions to environmental problems canbe divided into three groups:

� Business as usual: Doing nothing beyond the normal, economic growthwill solve all our problems.

� Natural capitalism:54 This group can, as a suggestion, be further sub-divided into the following groups:

– Ordinary environmental politics: Green investments, green subsidies,carbon taxes and similar taxes on natural resource uses.55

– Green GDP: Allow a green GDP – or more correctly speaking, a greenNDP56 – to grow, if it takes into account the depreciation of naturalcapital, which has been assigned appropriate economic values.57

– Performance economy: Build a market economy based on the sales offunctions instead of the sales of products, giving incentives for compa-nies to cut down the use of resources instead of making profits on thewaste of resources.58

� Steady-state economics: Transform the current economic system toan economy not built upon the principle of economic growth, and possiblydownscale the current economy to a sustainable level.59

53See Chapter 3.3.3 for details about the so called index decomposition analysis used inthis study. Whether growth contributes to decreased intensity can be analysed in a structuraldecomposition analysis, which will be suggested for future research.

54The term comes from Hawken et al., 1999, and subsequently used by many authors, likeRobert et al., 2002, and von Weizsacker et al., 2009. Here I use it in a broad sense for all marketfriendly solutions trying to solve the environmental problems.

55See UNEP, 2011 for a recent and optimistic investigation.56Net Domestic Product, i.e. GDP minus depreciation.57E.g. SOU, 1991:37, Simon and Proops, 2000.58This is an idea suggested in e.g. Stahel, 2010, and Stahel, 2007, and supported by many,

for instance in Rockstrom and Wijkman, 2011.59Jackson, 2009, Victor, 2008, and Daly and Farley, 2004, among others. See Malmaeus,

2011, for a model applied to the Swedish economy.

Chapter 3

Methodological framework

In this chapter we will go into the details behind the methods enabling a consump-tion perspective on a country’s environmental pressure. That means to lay thefoundations for the methodology of environmental input–output analysis uponwhich the consumption-based accounting approach normally is based. We willstart off with the national accounts, in which the input–output tables have theirorigin, continuing with the environmental counterpart to the national accountsnamely the environmental accounts. After that follows the environmental input–output analysis, which has its roots in the input–output tables of the nationalaccounts and the environmental data from the environmental accounts.

Chapter 3.1 and 3.2 dealing with the compilation of data from the national ac-counts and the environmental accounts, can be skimmed through or skipped forthe reader who wants to get straight to the methodology of the environmentalinput–output analysis described in Chapter 3.3. Furthermore, the purpose of thischapter is merely to give an overview of the methodology used in this area ofresearch, whereas the detailed method used in the study follows in Chapter 4.

3.1 The national accounts

The national accounts of a country is an accounting system for the flows and stockswithin a whole nation. It is similar to the accounting system of a company, butfor the national accounts, it’s about accounts on the country level. The nationalaccounts comprises not just the economy of the government or the public sector,but all the economic actors in an economy – accordingly the industry and thehouseholds are included as well, and also the economical transactions with therest of the world.1

The system of national accounts (SNA) is an international standard with its originwithin the UN system, recommending how the statistical offices of the member

1For more details, see e.g. Sandelin, 2005, and SOU, 2002:118.

19

20 Methodological framework Chapter 3

countries are to perform their national accounting. The standard has been devel-oped through a couple of revisions since the first version in the 1950s,2 and thelatest revisions are the 1993 SNA3 and the recently published 2008 SNA.4 EU hasdeveloped a more detailed standard, based on the last international standard 1993SNA, called the ESA 1995,5 and this is what the Swedish national accounts stilluses.6

The national accounts can be regarded as a collection of overlapping accounts. Oneof the most important economical statistics produced from the national accounts,is the GDP. Another important product of the national accounts, are the supplyand use tables (SUTs), and the input–output tables (IOTs), which are of particularinterest for this study.7

In the following sections, we will explain the SUTs, and how they are used togenerate the IOT which in turn forms the basis for the matrices used in input–output analysis. To be able to follow the reasoning, it is recommended to studythe SUTs and the IOT for Sweden 2005 in Appendix E. For the matrix algebraused, see Appendix C.

3.1.1 The supply table

The supply table corresponds to the supply side in the balance of supply and usedepicted in Figure 2.6. Compared with Figure 2.6, the supply table describes notonly the total flow of supplies, but gives also a sectoral resolution of this supplyflow. Additionally, the supply table includes both supply going to the industryand to the final consumers.

The supply table is principally made up of a product x industry table – called themake matrix – of products produced by the domestic economy, and an importscolumn of products produced abroad. In the make matrix, each column representsan industry, and each such column consists of the various products produced withinthat industry, with one product group on each row in that column. If we denotethe make matrix as S, this can be expressed as sij being the production of producti made by industry j.

Appended to the make matrix and the imports column in the supply table are alsoa column describing the conversion from basic prices to market prices,8 and totalcolumns. See Appendix E for the supply table for the Swedish economy in 2005.

2SOU, 2002:118.3UN et al., 1993.4UN et al., 2008.5EC, 1996.6Statistics Sweden, 2010.7Details about the SUTs and the IOT and the conversion from the SUTs to the IOT are

found in Miller and Blair, 2009, Eurostat, 2008, UN, 1999, and UN et al., 1993. The followingtext are mostly based on these sources.

8Basic prices are the values which the industries receive. Market prices, are the prices whichthe purchasers pay, which include taxes less subsidies on the products, money that the producerwont receive. See Statistics Sweden, 2010.

Chapter 3 Methodological framework 21

3.1.2 The use table

The use table corresponds to the use side of the balance of supply and use depictedin Figure 2.6. As in the supply table, the use table extends the description of theeconomy depicted in that figure, by giving a sectoral resolution of that use flow.But the use table doesn’t only describe the uses going to final consumption as inFigure 2.6, but also all the use of products going to the industry. This correspondsto the intermediate use higher up in the supply chain depicted to the left in Figure2.2 – this will be described in more detail further down. For an example of a usetable, see Appendix E with the use table for the Swedish economy in 2005.

The use table is made up of two main tables, a product x industry table on theleft hand side – called the intermediate matrix of the use table, or just the usematrix – and a final demand table on the right hand side. The former have, as inthe make matrix in the supply table, columns denoting the various industries in acountry. However, here the columns doesn’t consist of the products produced byeach industry, but the products used as inputs by each industry for the industryto be able to produce its products. This is sometimes called the production recipefor that industry to produce its products. If we denote the use matrix as U wecan, as in the corresponding case for S in the supply table, refer to uij as theproduct i used as input in industry j.

However, the industries do not only use products as inputs, but also labor forceand profits to the owners of the industries. This is shown in the row below theuse matrix, as a row of value added. Value added is the difference between whatthe industry earns when selling their products and the costs the industry have topay for products used as inputs.

Note that the column totals of the use matrix including the value added row,equals the column totals in the make matrix of the supply table. That is justbecause a particular industry’s total cost for inputs (including input of labor forceand profits to the owners), equals exactly, at least in theory, the total revenuesthe industry receives when selling their products.

The right hand side of the use table consists of the final demand table, dividedin columns for the various types of final demand. This calls for an explanation ofthe distinction between intermediate and final demand. Looking back into Figure2.2 once again, the arrows to the left represent the supply chain upstream fromthe consumer. This means that industries buy products from one and each otherin a supply chain, which downstream ends at the final consumers, i.e. the finaldemanders (the small dotted circle in Figure 2.2).9 The final consumers is final inthe sense that they don’t use what they buy for production, but for own purposes.The intermediate consumers on the other hand, are industries buying products forthe purpose of production.

Accordingly, looking for instance at the agricultural row in the use table, the cellsto the left in that row (the cells belonging to the intermediate matrix) represent

9Final consumer, final demander or final user are all used interchangeably in this text.


what the various industries purchase of agricultural products, i.e. the intermediatedemand of agricultural products. The cells to the right (the cells belonging tothe final demand table) represent what the final users purchase of agriculturalproducts.

The final demand is further subdivided into consumption (which could be privateor public), investments and exports. Investments can be regarded as long termconsumption which will later on be used in the production (e.g. buildings andmachines).10 Exports can be regarded as consumption made by actors abroad(the rest of the world).

The Swedish use table in Appendix E is in market prices. This makes sense,since the industry or the final user are, so to speak, not interested in whether themoney for purchasing products goes to the state as taxes, or to the producer of theproducts. However, it would also be reasonable to separate the taxes less subsidespart of all the costs an industry (or a final user category) have, by putting thesetaxes less subsidies on a separate row in the industry’s column. Then we wouldend up with a use table in basic prices and that is in fact how the input–outputtable normally is presented – see the following section for details.

3.1.3 The input–output table

The input–output table (IOT) can on the whole be regarded as a use table, butinstead of having industries as intermediate consumers in the columns of the inter-mediate use matrix, the IOT have products as the intermediate consumers. Thismay sound strange, but it is quite reasonable to imagine products as having inputsin order to be produced. It is also an essential part of the subsequent input–outputanalysis that the intermediate matrix in the IOT is a product x product matrix,of reasons that will be explained further on. See Appendix E for the Swedish IOTin 2005.

The terms input and output may need some further clarification. The inputs ofa product are the products and the labor force needed for its production – for agiven product, these inputs are shown on separate rows in that product’s column.It’s not just the inputs needed for one unit of that product, but the total inputsneeded to produce all products of that kind during one year (which in the case ofagricultural products in Sweden 2005 totals a value of 38 billion SEK). The inputscorrespond to what is used by different users or consumers, intermediate or final.In that sense, the inputs correspond to the use side of the balance of supply anduse depicted in Figure 2.6 (although in that figure intermediate uses have beenstripped and only final uses are shown, not all uses).

The outputs of a product are the different uses (intermediate as well as final) whichthat particular product is distributed to. I.e. for a given product these outputsare shown in separate columns on that product’s row. The output corresponds to

10This has implications for the input–output analysis, see later sections.


what is supplied, i.e. to the supply side in Figure 2.6 (although supply going tointermediate uses has been stripped from that figure).

Total inputs for all products are consequently found in a separate row below theintermediate matrix of the IOT. Total outputs for all products are found in aseparate column, to the right of the final demand table of the IOT.

Conversion of the use table to the IOT

To generate the IOT, mainly two methods are available depending on two differentassumptions. These assumptions deal with how the industries are converted to socalled homogeneous industries, i.e. imaginary industries producing only one prod-uct each. These homogeneous industries will correspond to the product columnsin the IOT. In this study, we will use the industry technology assumption, whichmeans that when the conversion from the use table to the IOT is done, it is as-sumed that each industry uses the same input structure (i.e. the same productionrecipe), for all kind of products that industry produce.11

When it comes to the question of market prices and basic prices, the followingtext works for both cases to the extent that the resulting IOT then is expressedin basic prices or market prices, respectively. Though, to be able to use the IOTfor input–output analysis, it must be in basic prices.

The conversion is done in the following way:12 Firstly, we will make use of thesupply table and the make matrix there within, denoted as S. We start off byconstructing a coefficient matrix of the make matrix called Sc by dividing all thecells in S with the column total from the column which that cell belongs to. If wedenote the row of column totals as xind, this procedure can be expressed as13

(3.1) Sc = Sx−1ind or (scij) = (sij/xindj ) .

This means that each row, denoting a product, in a column, denoting an industry,of Sc, is referring to the share of that product’s value to the total production valueof that industry. Or in other words, scij represents the share of the value of producti to the total production value of industry j.

The next step is the actual conversion, i.e. the transformation of the intermediatematrix in the use table to the intermediate matrix in the IOT. This is done bymultiplying the intermediate matrix U from the use table, by the transpose of Sc,

(3.2) F = US′c ,

where F is the intermediate matrix of the IOT. In F , element fij refers to thetotal inputs per year of product i needed for the total production of products oftype j.

11The other common assumption used, is the commodity technology assumption, which statesthat the same input structure is used for the same kind of product, whatever industry is producingthat product.

12This procedure is done in about the same way in Eurostat, 2008.13See Appendix C for an explanation of these kinds of operations.


How can this be understood? If one recalls the definition of matrix multiplication,when the U matrix is multiplied by the first column of S′c, it means that theinput structure (i.e. the column) of the agricultural industry is multiplied by theshare of agricultural products produced in the agricultural industry, plus, the inputstructure of the forest industry multiplied by the share of agricultural productsproduced in the forest industry, and so on. This procedure is repeated until we addup to the first column in F which consequently holds the generated input structurefor all agricultural products produced, whatever industry produced them. Thesame procedure is then followed for the other columns in S′c when U are multipliedby them.

Now we’re done with the intermediate matrix F of the IOT. The final demandtable – which, when its columns are added together, form the vector y – of theIOT is just the same as the final demand table of the use table, so all in all, wenow have completed the conversion of the use table to an IOT.

Dealing with imports

As yet, the use table and the corresponding IOT, haven’t included any informationabout the use of imports. The production recipe each industry or each productpossesses, should be understood as the inputs needed in total, no matter if theinputs are purchased domestically or from abroad as imports. When performingthe conversion to an IOT, the procedure explained above is the most easy task.The challenging part is to assess the domestic part and the imports part of all thecells in the IOT, a job done primarily by the national accounts offices based onextra trade data and qualified assessments. Since this is a quite demanding task,IOTs are normally not produced on a yearly basis – in Sweden it is done everyfive years.14

When the domestic–imports divide is done, the resulting IOT can be regarded asa table in three layers: the domestic layer, the imports layer, and the domesticplus imports layer. In the IOT in Appendix E these layers are all present directlyby presenting every cell as a domestic value + an imports value.

Updating IOTs

Since, as we said above, constructing IOTs are a quite resource demanding taskand therefore is not done on a yearly basis, a number of various techniques havebeen developed to do the updating of IOTs automatically. These techniques aremore or less based on extrapolating the information in an original IOT to themissing years, while at the same time calibrating the totals against the knowntotals of the missing years.15 In this study a variation of these techniques havebeen developed, which takes advantage of the information of imports shares fromthe original IOT – see Chapter 4.2.2 for details.

14Statistics Sweden, 2011a.15See Eurostat, 2008, for a good overview.


Physical IOTs

As was mentioned in Chapter 2, the rationale behind using monetary flows forestimating physical flows, is the fact that monetary values are much more readilyavailable. The monetary flows can then be regarded as proxies for the physicalflows, provided the correct conversions are done between price and e.g. mass. Thenormal way to do this, which will be explained in the following sections, is to dothe calculations as far as possible in monetary values, and then finish by convertingwith help of intensities. E.g. the total required production in the whole supplychain for some kind of final consumption is first calculated monetarily, and thenthis value is converted to a physical value.

Another possibility, which would be possible if more physical data was available,would be to directly use physical IOTs, where assessments of the physical inputsused for producing products are made. Some interesting research has been doneon this,16 but the prevailing method is still to use the former method described inthe preceding paragraph.

3.2 The environmental accounts

In the previous sections we have been talking about the national accounts, andanalysed their most important products for this study, the supply and use tables,and the input–output tables. Appended to the system of national accounts, arealso so called satellite accounts, which are not a completely integrated part of thenational accounts, but still are developed in order to be able to use them togetherwith the national accounts to as high a degree as possible. The environmentalaccounts is such a satellite accounting system.

In the SNA 1993 the use of satellite accounts, in particular environmental accounts,was introduced. In 1993, UN also came with its first publication dealing with asystem of integrated environmental and economic accounting, SEEA 1993,17 whichnow has been updated to the SEEA 2003.18

In Sweden the environmental accounts system has its origin in the Commission forEnvironmental Accounting appointed in 1990,19 leading to the establishment of theenvironmental accounts in Sweden, which have been in use since 1993. In Sweden,Statistics Sweden, the National Institute of Economic Research, and the SwedishEnvironmental Protection Agency have been responsible for the environmentalaccounting.

16In Stahmer, 2000, not only a physical IOT is constructed but also a time IOT. Daly, 1968,constructs a physical IOT where not only inputs and outputs from and to the biosphere isincluded, but also the input and output flows within the biosphere (less the society). See alsoWeisz and Duchin, 2006.

17UN, 1993.18UN et al., 2003.19SOU, 1991:37.


The main purpose of the environmental accounting system is to organize statis-tics on environmental data (e.g. resource flows and emissions flows) in a way thatmake these data compatible with the national accounts. That means to classifyenvironmental data into the same industrial categories as used by the nationalaccounts, in order to be able to compare economical and environmental perfor-mance of the various industries of a country (e.g. calculate emission intensities).Earlier environmental statistics have not done this. This work goes under theheading physical environmental accounts, and in Sweden this is the responsibilityof Statistics Sweden.20

Other important purposes of the environmental accounting system, is to try tovaluate natural resources, and to develop a green GDP. This is called the mone-tary environmental accounts, and in Sweden the National Institute of EconomicResearch has the responsibility for this work.21

3.2.1 Integrating national and environmental accounts

Statistics from the national accounts and from the environmental accounts can bepresented in an integrated matrix form, as seen in Figure 3.1. This is sometimescalled a NAMEA (National Accounting Matrix with Environmental Accounts).22

Figure 3.1 consists of the input–output table, extended with an environmentalmatrix shown below (the two boxes in the lowermost part of the figure).23

Intermediatematrix, Fd + Fm

Final demand,yd + ym

Totaldom.output,xp

Taxes, less subs.Value added

Total input, xp

Environmentalmatrix, Ep

Product 1Product 2...

Pro

duct

1P

rodu

ct 2

... Con

sum

ptio

nG

ross

inve

stm

ents

Exp

orts

Resource use or emissions 1Resource use or emissions 2...

Environmentaldirect use, edir

Totalimp.,m

Figure 3.1. The structure of economic and environmental data into one framework, aNAMEA. Source: Based on Statistics Sweden, 2000.

20SOU, 1991:37, Statistics Sweden, 2002a, and Peters, 2008.21SOU, 1991:37, and Statistics Sweden, 2002a.22UN et al., 2003.23Based on Statistics Sweden, 2000.


Some notes regarding Figure 3.1 are needed. The environmental direct use edir

below the final demand box, consists of the resource use and emissions generatedin the usage phase of the products, i.e. downstream after consumption. That isenergy use and emissions occurring e.g. for heating of housing and transports.All downstream environmental impact is however not part of edir; environmentalimpact during the disposal phase is instead considered impact happening upstreamin the waste industry, whose products are waste services.

Furthermore, to be more theoretical consistent, resource uses ought to be theonly environmental parameters shown below the intermediate matrix, since thesecan be regarded as inputs. Analogously, the emissions ought to be found to theright of the table, as outputs. However this is not the case, since in practice, theenvironmental matrix Ep is one continuous table in the environmental accounts.Also, it would be hard to show the direct emissions from final users in that way,as there is no output row for final users.24 It is also possible to interpret emissionsas resources – for instance the emissions of CO2 can be considered being a use ofthe carbon absorption capacity resource of the atmosphere – so in that sense it isreasonable to have all environmental parameters as inputs.

3.2.2 Environmental data per industry and per product

In Figure 3.1, the environmental matrix Ep consists of rows representing energyuses and emissions, and columns representing products using these energy re-sources or emitting these emissions. I.e. epij is the energy use type or emission typei used or emitted by product j. However, since the original environmental data inthe environmental accounts is presented per industry in a corresponding matrixEind, we need to convert this matrix first in order to get Ep. This is done in away that resembles the conversion of the use table to an IOT.25

To get Ep, we postmultiply Eind by S′c as is done in the following:

(3.3) Ep = EindS′c .

This can be understood in the same manner as in the SUT–IOT conversion. Thatis, the first column in Ep is generated by taking the emissions column from theagricultural industry in Eind multiplied by the production share of agriculturalproducts in the agricultural industry (i.e. the first element of the first column ofS′c), plus the emissions column from the forest industry in Eind multiplied by theproduction share of agricultural products in the forest industry (i.e. the secondelement of the first column of S′c), and so on, until we have all the emissionsthat the agricultural products generate. The other columns of Ep are generatedanalogously.

24Although, Daly, 1968, designs a households row corresponding to the final consumptioncolumn, and is in this way able to construct physical inputs and physical outputs in this moreconsistent way.

25Ostblom, 1998, does this in an equivalent way.


3.3 Environmental input–output analysis

Until this point, we have described how the data used in environmental input–output analysis are organized and collected, by the use of economic data fromthe national accounts and the use of environmental data from the environmentalaccounts. The result of this organization is summarized in Figure 3.1. Eventhough some of the data went through some processing – e.g. when the conversionto the input–output table (IOT) was done, and when the environmental data perindustry were converted to environmental data per product – a regular analysishas not really been done yet. That is the task for the following sections, which willgo into the details of the input–output analysis and its environmental extension.

The input–output analysis method was developed by the economist Wassily Leon-tief,26 and earned him the Nobel Prize in economics in 1973.27 Since 1988 the Inter-national Input–Output Association is active and responsible for e.g. the scientificjournal Economic Systems Research, specialized in research about input–outputanalysis.28

3.3.1 Foundations of the input–output analysis

Domestic production and the Leontief inverse

We will start off with the pure economic part of the input–output analysis, byfirstly returning to the input–output table from the national accounts.29 Lookingat the domestic part of the IOT, this table can mathematically be expressed as

(3.4) Fd i + yd = xp ,

where F d is the domestic part of the intermediate matrix of the IOT, i is a unitvector, yd is the domestic part of the final demand, and xp is the total output,i.e. the total value of the various products produced over a year.

For the sake of the analysis, we’re now interested in expressing the intermediatematrix Fd as a coefficient matrix, i.e. the domestic inputs expressed as shares oftotal input (or as shares of total output, since total input equals total output).Or, in other words, the value of the various domestic inputs per dollar’s worth ofproduced output. This gives us the matrix

(3.5) Ad = Fd x−1p ,

called the matrix of technical coefficients, where each of the elements adij = fdij/x

pj

expresses the value of domestic product i needed as input per dollar’s worth of

26First presented in Leontief, 1941.27Another Nobel Prize in economics for the work in the IOA field was given to Richard Stone

in 1984. See UN, 1999.28IIOA, 2011.29This follows more or less the text of Miller and Blair, 2009, and UN, 1999.


produced output of product j. This matrix describes the industry structure of anation for a given year as regards domestic production, and it is assumed to befixed, i.e. the relations between the industries are assumed not to change. Thisis reasonable if not too many years have past, or the production volume of theeconomy has not changed substantially. Concretely speaking, this means that wecan multiply Ad with any vector of products we want to be produced, and theresulting vector will correctly show all the direct inputs needed to produce thoseproducts. In other words, linearity is assumed since any vector of products wewant to be produced, use the same industry structure.

Now it also becomes clear that the intermediate matrix in the use table need beconverted to the product x product intermediate matrix in the IOT, in order tomake it possible to multiply the Ad matrix with a product vector in a meaningfulway. From the above and from what follows below, it is also evident that the IOTmust be in basic prices, so that Ad only reflects the pure inputs needed, excludingtaxes (e.g. inputs of inputs would otherwise be valued too high, since also the taxpart would have inputs, which is not the case).

Now, with the help of equation (3.5), it is possible to express equation (3.4) in thefollowing way:

(3.6) Adxp + yd = xp .

Rearranging gives us

(3.7) xp = (I −Ad)−1yd

which means that if Ad is fixed, the total output xp can be considered a functionof the final demand yd which can be chosen arbitrarily.30 In other words, equation(3.7) expresses the total domestic output needed throughout the whole supplychain to satisfy the final demand yd.

How can we understand that equation (3.7) describes the production neededthroughout the whole supply chain more intuitively? Imagine that the products yd

are consumed. The direct production needed to satisfy this consumption will thenbe just yd, or let us express it as Iyd = yd. What products are needed indirectlyto be able to produce yd? Now, look back to what the matrix Ad meant: everycolumn in Ad describes the inputs needed per dollar’s worth of produce. So if wetake Ad and postmultiply it by yd, we would, remembering how matrix multipli-cation is defined, actually get the total inputs needed to be able to produce all theproducts in the vector yd. So the vector Adyd expresses the production needed inthis step of the supply chain to produce yd. But how much production is neededin the next step – to produce Adyd, what will the inputs be then? Remember nowthat Adyd is the new consumption vector, and we will now see how much inputsare needed to be able to satisfy the consumption Adyd. That is obtained by onceagain postmultiplying Ad, this time by Adyd, which gives us the production A2

dyd

in this step of the supply chain.

30Even though an arbitrarily chosen final demand yd differs from the fixed final demand yd

of the IOT in equation (3.4) we will use the same notation. Analogously with the output xp.


This procedure can be repeated infinitely, and if we add together all this productionproduced in each step in the supply chain, as explained above, we will get the totalproduction needed to satisfy the consumption yd as

(3.8) (I + Ad + A2d + A3

d + . . . + And)yd = xp .

Now, can this infinite series inside the parenthesis on the left hand side of equation(3.8) be expressed in a more convenient way? As a matter of fact it can. If wepremultiply the parenthesis with (I −Ad) we get31

(I −Ad)(I + Ad + A2d + . . . + An

d) = (I + Ad + A2d + . . . + An

d)

− (Ad + A2d + A3

d + . . . + An+1d )

(I −Ad)(I + Ad + A2d + . . . + An

d) = I −An+1d = I , n→∞

(I + Ad + A2d + . . . + An

d) = (I −Ad)−1 ,

(3.9)

assumed that An+1d → 0, as n→∞.32

So equation (3.8) can actually be expressed as

(3.10) xp = (I −Ad)−1yd ,

and that is the same result as was obtained in equation (3.7) which means that theinterpretation of the supply chain offered by the reasoning behind equations (3.8)and (3.9) must be correct. The infinite series I +Ad +A2

d + . . . is the power seriesapproximation of (I −Ad)

−1 and is known as a power series, or more specifically,as a geometric series,33 here in matrix form.

In other words, an arbitrary final demand yd results – directly and indirectlythroughout the whole supply chain – in the total production that amounts to xp.As was indicated earlier, this is true under the assumption that the input structuregiven by Ad is fixed and exactly the same wherever we are in the supply chain,and whatever production is produced in the various steps of the supply chain.

The matrix (I −Ad)−1 is the so called Leontief inverse, and we will from now on

denote this as Ld = (I−Ad)−1. Looking at equation (3.8) and (3.10) carefully, Ld

can be regarded as a matrix composed of an infinite number of layers, each layerrepresenting each of the terms in the power series approximation I+Ad+A2

d+ . . ..This yields us an interpretation of the elements in Ld, where a column representsall the direct and indirect production needed to satisfy the consumption of onedollar of the product which that column represents, with the required productionper product on the various rows in that column. Or, in other words, ldij is the totaldirect and indirect production of product i to satisfy the consumption per dollar’sworth of product j.

31See Miller and Blair, 2009. This result can also be achieved by going backwards from thestandard Maclaurin series of (1− x)−1 – see Adams, 1995.

32This is plausible, since all elements in Ad are less than 1. However, a formal proof ispresented in Appendix D.

33Adams, 1995.


Total production including trade

In the previous section, we only discussed the required production produced do-mestically to satisfy some kind of final demand of domestic products. In this sec-tion we will also discuss the required production produced abroad to satisfy thetotal final demand. In consumption-based accounting studies related to environ-mental pressure, there are in essence two methods when calculating the productionabroad needed to satisfy final demand – single-regional input–output (SRIO) anal-ysis and multi-regional input–output (MRIO) analysis.34 We will briefly describeboth of them below, and also examine the production needed domestically for theexports part of the final demand. But first, we will start off with some generalconsiderations regarding imports in input–output analysis.

If we are to include the imports part of the IOT, it is possible – as we did inequation (3.4) for the domestic part – to express the IOT mathematically as

(3.11) (Fd + Fm)i + (yd + ym) = xp + m ,

where Fm is the imports to the industry, ym the imports to the final consumers(i.e. the final demand of imports), and m is the total imports with m = Fm i+ym.

This means that the matrix of technical coefficients really should be expressed as

(3.12) Atot = Ad + Am = (Fd + Fm)x−1p

in order to properly describe the production recipes used in the production ofall the products, i.e. a production recipe including both domestic and importedinputs. Thus, atotij = (fd

ij + fmij )/xp

j , represents the total direct input (domesticand imported) of product i needed in the production of product j. Combiningequation (3.11) and (3.12) means that the total IOT can be expressed as35

(3.13) (Ad + Am)xp + (yd + ym) = xp + m .

To obtain Atot it is important not to divide the cells in F tot (= Fd + Fm), e.g.cell f tot

ij , with the total supply of product j in the vector (xp + m) even though(xp +m) is the vector of row sums of the whole IOT described by equation (3.13).In other words, atotij 6= f tot

ij /(xpj +mj). This is because the domestic products’ input

shares (even though imports are included in those input shares) should still be inrelation to the domestic products’ output, not in relation to the products’ supply(which includes imports of already produced products). The latter would yielda matrix which is not describing the domestic industry structure or the domesticindustries’ production recipes. In the IOT in Appendix E, this corresponds todividing by 38 billion SEK and not 52 billion SEK in the agricultural productscolumn.36

34Wiedmann, 2009.35UN, 1999.36This is discussed in e.g. Ostblom, 1980, and Bergman, 1977. If information of the domestic–

imports proportions was insufficient in the IOT, this would not be a trivial fact.


Single-regional input–output analysis SRIO analyses include the rest of theworld (ROW) by assuming it has the same technological structure as the modelledcountry, e.g. as the Swedish technological structure. That means that the requiredproduction to produce the imported products is calculated by using the technicalcoefficients matrix of the modelled country. This is a quite strong assumption,since the inputs needed to produce a certain product in other countries coulddiffer quite substantially. But when using SRIO modelling, it is the only optionavailable.

Various SRIO analyses use various approaches to the ROW.37 Some studies withthe purpose of only analysing domestic effects of the consumption, does accordinglynot include the effects abroad at all. Some studies use Ad to model ROW, otherAtot = Ad + Am, which would be the most correct method, since Ad doesn’tdescribe the total direct inputs needed in the production recipes.

To express mathematically the production needed throughout the whole supplychain domestically and abroad to satisfy the total final demand yd + ym – giventhat the ROW is approximated by Atot – the power series approximation of theLeontief inverse is helpful. In Figure 3.2 this is visualized as a binary tree. In thetop of the tree, final demand, ytot, is first divided into a domestic part, yd, and animported part, ym. The domestic branch to the left is then further divided intodomestic production, Adyd, and imported production, Amyd. For the importedbranch to the right, the same is done, however the division in Adym and Amym

is really not needed, since we’re already abroad.

The total production caused by ytot is the sum of all nodes in the whole tree, whichcan be expressed as Ltotytot = (I+Atot+A2

tot+. . .)ytot. The production occurringdomestically due to ytot is the sum of all nodes on the left edge of the whole tree,in other words Ldyd = (I + Ad + A2

d + . . .)yd. The production occurring abroadis accordingly the sum of the whole tree, less the left edge, i.e. Ltotytot − Ldyd.

38

Note that in all these sums, the top node of the tree is always excluded, since itis already counted at the second level of the tree.

ytot

Iyd Iym

Adyd Amyd Adym Amym

AdAdyd ... ... ... ... ... ... ...

Figure 3.2. Binary tree describing production occurring domestically and abroad inthe whole supply chain to satisfy final demand of domestic and imported products.

37See e.g. Lenzen, 1998, Ostblom, 1998, Machado et al., 2001, and Lindmark, 2001.38This result is also used in Finnveden et al., 2007.


Accordingly, this gives us a way of separating the required production occurringdomestically and abroad. That separation will be used in this study when domes-tical and ROW production will be attributed different resource use and emissionintensities. However, imports that has been exported from the modelled countryfurther back in the supply chain will then wrongly be included in the ROW part– so called feedback effects – which implies that the higher ROW intensities willbe used on a slightly too big share of the total production Ltotytot.

Multi-regional input–output analysis In MRIO studies, the A matrices ofthe trading countries in the ROW are known to some extent; also known is thedistribution of imports over the countries exporting to the model country.39

Mainly two methods are used in MRIO analysis.40 The first, the unidirectionaltrade model, separates the imports vector m into different imports vectors, onefor each trading partner who is exporting products to us. These vectors mi forvarious countries i, are subsequently premultiplied by the exporting countries’ Ad

matrices. In this way the production needed for the imports to be produced insidethe trading countries are included, but not the production these trading countriesin their turn need from their trading countries.

The second MRIO method, the multidirectional trade model, takes care of this, asit in theory uses all trading countries’ A matrices, and information about how theytrade. This is implemented by setting up a block matrix of A matrices, so that forevery country, the Am matrix for that country is divided into separate Am matricesfor each country they are in turn importing from. These models also take care ofthe feedback effects resulting from exports exported to one country, which afterbeing processed, are imported back to the first country.41 The multidirectionalMRIO model has been implemented in the GTAP database42 which a number ofstudies have been using.43

Exports In consumption-based accounting studies, the purpose is to reallocatethe responsibility of the production to the citizens of the country causing thatproduction. Therefore, exports, i.e. production caused domestically due to theconsumption done by actors in the rest of the world, should not be part of themodelled country’s required production. Accordingly, final demand ytot shouldexclude exports. We will denote this as ynexp

tot .

39Weber and Matthews, 2007, distinguishes these as the two major types of data needed inMRIO models.

40Lenzen et al., 2004, Peters and Hertwich, 2009.41de Haan, 2002, and Peters and Hertwich, 2009.42GTAP, 2011.43E.g. Peters et al., 2011, Peters and Solli, 2010, and Davis and Caldeira, 2010. See Wied-

mann, 2009, for an overview.


3.3.2 Environmental extension to input–output analysis

We have now discussed the methods to determine the total production neededupstream all throughout the supply chain, domestically as well as abroad, to sat-isfy the total final demand in a country. Now we’re heading for the main goal inthe analysis, and that is to see what environmental repercussions that productioncauses – the consumption perspective on environmental impact. That is the sub-ject of the environmental extension to the input–output analysis (environmentalIOA).44 See Chapter 2.1.2 and Figure 2.2 for the rationale behind this subject.

To translate flows of production from the IOA to flows of masses in the environ-mental IOA, the environmental intensities of production is utilized (see discussionin Chapter 2.2.2). E.g. the amount of CO2 emitted per dollar’s worth of some typeof product is calculated. In Chapter 3.2, we learned that through the environmen-tal accounts, the total flows of resource uses and emissions generated in the variousindustries were collected in an environmental matrix called Eind. This matrix wastransformed to the matrix Ep in order to see the resource uses or emissions pertotal production of a certain product, during a year. To get the correspondingenvironmental intensity matrix Ei, all resource use or emission types in a columnof Ep is divided by the corresponding production value of that product to whichthat column refers, i.e.

(3.14) Ei = Epx−1p .

Thus, an element eiij in Ei refers to the resource use intensity or emission intensityof resource use or emission type i in the production of product j.45

Having generated Ei means that it is possible to calculate the consumption-basedresource uses and emissions for multiple resource use or emission types all at once,in a single matrix multiplication. This is done, postmultiplying Ei by the requiredproduction from some final demand, as expressed in equation (3.10), i.e.

(3.15) ec = EiLy ,

where ec is a column vector denoting the consumption-based environmental im-pact, with eci referring to the amount of resource use or emissions of type i gener-ated through the whole supply chain, caused by the final demand of all products.46

Equation (3.15) is the central equation of the environmental IOA used in this study.

In some SRIO studies,47 Ld is used for L and yd is used for y, meaning that thedomestic causes of final demand (inclusive exports) are analysed (impact on ROW

44See Leontief, 1970, for one of the first accounts of the subject. Miller and Blair, 2009, givesan overview. See e.g. SEI, 2010, and SEI et al., 2009, for current and recent projects usingenvironmental IOA.

45Ostblom, 1998, is doing this in a similar way.46See Miller and Blair, 2009. However, as is pointed out by Miller and Blair, caution must

be done when calculating energy use in this way, if both primary and secondary energy uses arecalculated. Blair, 2011, confirms though, that when using only primary energy uses (as is donein this study), equation (3.15) is correct.

47E.g. Ostblom, 1998.


not included). Some other studies use Ltot (or Ld) and ynexptot or similar approaches,

in order to analyse the worldwide causes of the domestic final demand (exclusiveexports).48

In unidirectional MRIO studies, ec in equation (3.15) is calculated for every export-ing country from which the modelled country are importing, with country-specificintensities and Leontief inverses (Ei and L) and different y’s (denoting imports)depending on country; then all these country-specific ec vectors are summed to-gether.49 In multidirectional MRIO studies a block matrix is applied as mentionedearlier, and every country are assigned country-specific intensities.50

In many consumption-based studies, downstream effects are also part of the analy-sis by including the direct use edir in equation (3.15), thereby considering resourceuse and emissions in the usage phase as well.51,52 Downstream effects in the dis-posal phase are already a part of the analysis upstream, since these effects can beconsidered included in the consumption of waste services from the waste industry.

LCA versus IOA

Since environmental IOA through its Leontief inverse, determines the environmen-tal pressure caused throughout the whole supply chain, without any theoreticalsystem boundary, it could be used together with ordinary life cycle assessments(LCAs). LCAs are still superior when it comes to determine the environmentalimpact early in the supply chain of some specific product, since the analyses donethere are pretty detailed. However, it is impossible to extend the process tree ofan LCA for ever, since the data demands become to high. Therefore, IOA canbe used to cover up the rest of the process tree. IOA, on the other hand, cannotbe used as a substitution for LCA, since the IOA only gives an average value ofthe pressure caused by a whole product group, whereas a LCA analyses a specificproduct. In general, LCAs are more relevant for analyses on a specific productlevel, whereas IOAs are more relevant on a country level.53,54

Ecological footprints and other embedded concepts versus IOA

The ecological footprint is an analytical tool for determining the land area neededto produce the products consumed and absorb the waste and emissions producedby a whole country.55 The ecological footprint takes into account imports and

48E.g. Lenzen, 1998, and Statistics Sweden, 2000.49See e.g. Peters and Hertwich, 2006.50See references in previous section about MRIO analysis.51E.g. Ostblom, 1998, Carlsson-Kanyama et al., 2007, and Swedish EPA and Statistics Swe-

den, 2008.52See Chapter 3.2.1 regarding edir.53See Hendrickson et al., 2006, for a good introduction. Peters, 2010, and Finnveden and

Moberg, 2005, discuss country-level to product-level issues, and hybrid models. Also discussedin Spreng, 1988.

54See also Chapter 2.1.2 for a comparison between LCA and IOA.55Introduced in Rees, 1992, and Wackernagel and Rees, 1996. See also WWF, 2010.


exports, but not the indirect effects through the whole supply chain like the IOAdoes. However, recent research has proposed a developed ecological footprintanalysis combined with IOA.56

In this context the concept of virtual water and similar embedded concepts likeemergy need mentioning. The analysis of these concepts in relation to IOA willbe suggested for further research.57

3.3.3 Time series and EKCs based on input–output analysis

Overview and studies performed

Most environmental IOA studies have been studying single years only,58 but thereare some exceptions. In a study by Weber and Matthews, the emissions embodiedin US trade for the years 1997, 2002 and 2004 are analysed using an unidirectionaltrade MRIO.59 Roca and Serrano study Spanish pollution for the years 1995 and2000, using a SRIO model.60 In a Nordic council study from 2010, Peters and Sollistudy the Nordic countries using multidirectional MRIO analysis for 1997, 2001and 2004.61 Wiedmann et al., construct a time series from 1992–2004 for the UK,using a unidirectional MRIO.62 Recently, Peters and colleagues performed a MRIOtime series analysis covering the period 1990–2008 for embodied CO2 emissions intrade between developing and developed countries.63 The general results from allthese studies show increasing emissions, and in general higher levels compared toofficial production-based data.

For the sake of performing IOA-based EKC studies, time series are needed whenperforming longitudinal analysis for a certain country. However, IOA-based cross-sectional analysis is also an option when performing EKC studies. This is done byHertwich and Peters who perform a cross-country study utilizing multidirectionalMRIO analysis, covering the whole world.64 In a study by Davis and Caldeira across-country analysis is also performed, though no EKC analysis is performed –although, it can be shown from their data, that there exists no EKC-like pattern,and CO2 emissions are rising with increasing GDP.65 In the Roca and Serranostudy above a cross-sectional EKC analysis is also performed over increasing in-come groups – results suggest absolute decoupling does not occur.66

See Chapter 3.3.4 for Swedish studies.

56See Wiedmann et al., 2006, which also gives an overview of the ecological footprint literature.57See Lenzen, 2009, for an IOA study concerning virtual water.58Peters and Solli, 2010.59Weber and Matthews, 2007.60Roca and Serrano, 2007.61Peters and Solli, 2010.62Wiedmann et al., 2010.63Peters et al., 2011.64Hertwich and Peters, 2009.65Davis and Caldeira, 2010.66Roca and Serrano, 2007.


Decomposition analysis

When constructing time series of environmental pressure, it is of interest to decom-pose the various factors contributing to the change of the environmental pressure.For instance, looking at the IPAT equation, the impact I is multiplicative decom-posed into the factors P , A and T . It is also possible to decompose I additivelyinto contributing terms that individually correspond to P , A and T – this will beshown below in the case of two variables.

The most common form of decomposition analysis is index decomposition analysis(IDA), dealing with environmental factors which are not based on IOA and theLeontief inverse. Structural decomposition analysis (SDA), on the other hand, isa method for decomposing factors in IOA-based studies.67

Multiplicative decomposition measures the relative change in a variable, and is,as the case for the IPAT above showed when the analysis was not done witha sectoral resolution, straightforward. Additive decomposition, measuring theabsolute change in a variable, requires some examination though. Suppose wehave a simplified form of IPAT relation, say emissions (e) of CO2, depending onvolume (v) in GDP, and on intensity (i) expressed as CO2/GDP. Then we have

(3.16) e = vi .

The idea behind additive decomposition is to find out how much e would changedue to the change of v given that i remains unchanged, and how much e wouldchange, due to the change of i given that v remains unchanged.68 In other words,we would like to express ∆e = ∆(vi) as ∆e = f(∆v) + g(∆i). This can be derivedby expressing the total derivative of e when e is a function e(v(t), i(t)) = v(t)i(t).Differentiation gives69

(3.17)de

dt=

∂e

∂v

dv

dt+

∂e

∂i

di

dt⇔ de =

∂e

∂vdv +

∂e

∂idi ,

and considering that e = vi, the partial derivatives become ∂e∂v

= i and ∂e∂i

= v, soequation (3.17) transforms to

(3.18) de = idv + vdi .

So for a small change in e we have actually decomposed e into two terms, the firstterm depending only on changes in v, the other term depending only on changesin i.

If considering the two-dimensional surface that the function e(v, i) = vi describesin the diagram in Figure 3.3, the terms of de describe the change happening in e,

67See Wood and Lenzen, 2009, Hoekstra and van der Bergh, 2003, and Ang and Zhang, 2000for overviews and literature surveys. Minx et al., 2009, is a recent SDA study for UK CO2

emissions.68Kander, 2002, calls this counterfactual analysis, i.e. what would the change in impact have

been, if one of the independent variables had been constant.69Hoekstra and van den Bergh, 2002, and Adams, 1995.


0 0.5 1 1.5 2 0 0.5 1 1.5 20

1

2

3

4

iv

e1

e0

Figure 3.3. Plot of the surface e(v, i) = vi.

i.e. the change in height above the v, i-plane (the floor of the box in the diagram),when going on the surface e(v, i) = vi the infinitesimal distance from the startpoint e0 to an end point infinitely close to e0. This distance is accomplished bygoing along the surface for instance the distance dv in the v-direction, and thedistance di in the i-direction. Thus, going the distance dv in the v direction, leadsto the increase idv in height above the v, i-plane, and going the distance di in thei-direction, leads to the increase vdi in height above the v, i-plane, all in all leadingto an increase in height that amounts to de = idv + vdi as described by equation(3.18).

The distance on the surface from e0 to a point infinitely close to e0 could alsobe accomplished by first going the distance di in the i-direction, and then thedistance dv in the v-direction. However, these two ways of getting from e0 to thepoint infinitely close to e0 are unambiguous, since the function e can be consideredto be a plane for infinitesimal changes.

However, when discretization of equation (3.18) is done, we get for instance

(3.19) ∆e = i0∆v + v1∆i ⇔ (e1 − e0) = i0(v1 − v0) + v1(i1 − i0).

Consider the surface e(v, i) again in Figure 3.3. The arrows indicate one of thepossibilities of how to get from the starting point, e0, to the endpoint, e1, in thediscrete case, by first going in the v-direction, and then in the i-direction – thisalternative is also what equation (3.19) describes. However, there is also anotherpossibility, not shown in the diagram, and that is to, starting at the same pointe0, instead first go in the i-direction, and then in the v-direction, to end up at e1.Accordingly, since e(v, i) is a non-linear function, there are two ways of going frome0 to e1, and thereby two ways to discretize equation (3.18). A common solutionis to use the average of these two ways:70

∆e = i0∆v + v1∆i = i1∆v + v0∆i(3.20)

=1

2(i0∆v + i1∆v) +

1

2(v1∆i + v0∆i) .(3.21)

70See Dietzenbacher and Los, 1998, and Miller and Blair, 2009. A number of other moresophisticated methods are available, see e.g. Hoekstra and van der Bergh, 2003.


We can now conclude, by saying that the change in ∆e = f(∆v) + g(∆i), wherethe functions f and g are given by the two terms of equation (3.21). Whendecomposing into more variables, the same approach as above is used. To arriveat the percentage contributions of the components, division by e0 is done as in

(3.22) 100 · ∆e

e0= 100 · f(∆v)

e0+ 100 · g(∆i)

e0.

Applying this for IOA studies, i.e. performing structural decomposition analysis(SDA), yields that e.g. equation (3.15), i.e. ec = EiLy, can be decomposed forinstance as

(3.23) ∆ec = E0iL

0∆y + E0i ∆Ly1 + ∆EiL

1y1 .

It may at first seem strange in e.g. the second term above, to take the differenceof L, which is a matrix, when the difference ∆ec is a vector. That is however notany problem, since the second term is in fact (E0

iL1y1−E0

iL0y1) which is indeed

a vector.

SDA is however only meaningful if the IOTs and subsequently L1 and L0 areavailable in constant prices. In this study we have not been able to obtain IOTsin constant prices, and consequently a SDA will not be performed. An IDA willhowever be performed, based on the results in equation (3.21) and (3.22) – seeChapter 4.4.3.

3.3.4 Swedish studies

Most of the studies utilizing IOA for estimating the environmental pressure causedby the Swedish economy, analyse a single year only. In 1998, Ostblom madea study of CO2, SO2 and NOx comparing them with Sweden’s environmentalgoals.71 In 2000, Statistics Sweden, analysed CO2, SO2 and NOx.

72 In 2007,Carlsson-Kanyama et al., made a study of CO2 using among others data from mul-tidirectional MRIO databases.73 The Swedish Environmental Protection Agencyperformed a similar study in 2008.74

Swedish IOA-based time series analyses are few. Decomposition analyses wasperformed in studies by Bergman75 and Ostblom76 who analysed the change inSwedish energy use during the sixties and the seventies. Kander and Lindmarkhas performed long-term longitudinal studies for CO2 covering up to two hundredyears, though the IOA performed only include the twentieth century. They also

71Ostblom, 1998.72See Statistics Sweden, 2000 and an updated English version in Statistics Sweden, 2002b.73Carlsson-Kanyama et al., 2007.74Swedish EPA, 2008. Also referred to in Swedish EPA, 2010a, and Swedish EPA, 2010b. See

Swedish EPA and Statistics Sweden, 2008, for detailed methods.75Bergman, 1977.76Ostblom, 1980.


perform an EKC study based on their data.77 Statistics Sweden made a SDAstudy in 2003 of CO2.

78 Finally, in 2010 a study based on multidirectional MRIOfor the years 1997, 2001 and 2004 was published.79

Most of these studies, show higher levels of pollutants compared to official pro-duction-based data, and in the latest MRIO study from 2010, emissions increasedwith time.80 An exception is the long term studies by Kander and Lindmarkmentioned above, though this is probably due to the employment of a SRIO modelwith Swedish emission intensities for the production occurring abroad.

The study presented in this report, will add to the earlier Swedish IOA-based timeseries analyses, by analysing, among others, the consumption-based emissions ofCO2 equivalents for a complete time series (1993–2005). This study will alsotest the EKC hypothesis against the development of the consumption-based CO2

equivalents, which hasn’t been done before on Swedish data. See Chapter 4 fordetails.

3.3.5 Uncertainties

Not so many studies have been performed analysing uncertainties in environmen-tal input–output models.81 The uncertainties range from aggregation errors82 toincomplete data or data of low quality. The latter applies for instance in all thecases where input–output tables are not available for all years, or for all countrieswhich a particular study analyses – in other words, a prevailing problem in allenvironmental IOAs.

The linearity, which is the basis of the input–output analysis, can be understood asan assumption introducing uncertainties in the results when final demand differsa lot from the original final demand from which the technological matrix origi-nated. However, this ought to be a problem only in change-oriented studies orprojections, where an analysis of the effects of some certain change on the marginis performed. In contrary, this present study could be considered as an accountingstudy, whose purpose only is to allocate the energy use or emissions which alreadyhave occurred.83

The problem of uncertainties in studies making use of exchange rates betweencountries – which is almost always the case in MRIO modelling and in some

77See Lindmark, 2001, and Kander and Lindmark, 2006.78Statistics Sweden, 2003. Statistics Sweden also has a time series of CO2 emissions available

on their web page, see Statistics Sweden, 2011h.79Peters and Solli, 2010.80Ibid.81See Wiedmann, 2009, for a literature survey. Hendrickson et al., 2006, gives an introduction

to the subject, showing how Monte Carlo simulation can be employed.82See Kymn, 1990, and Miller and Blair, 2009, for an overview of the aggregation problem

in input–output analysis in general. Lenzen et al., 2004, analyses the problem of aggregation inconnection to environmental IOAs.

83Finnveden and Moberg, 2005, make this distinction. In Brander et al., 2009, a similardistinction is made between consequential and attributional approaches to LCA studies.


cases in SRIO modelling as well – have been discussed by e.g. Weber in a studyof the embodied emissions in US international trade. In Weber’s study, usingpurchasing power parity (PPP) exchange rates for valuing products instead ofmarket exchange rates (MER), yields almost 50 percent lower emissions.84

In this study uncertainties will be studied to the extent that the results are pre-sented based on the PPP approach, with the Swedish intensities abroad approachand the MER approach as lower and upper bounds respectively.85

3.3.6 Other topics

A consideration in input–output models not discussed so far is the extent to whichinvestments are used as inputs in the industry. The usual input–output table (e.g.the Swedish 2005 IOT, see Appendix E) doesn’t consider investments as beinginputs in the intermediate matrix, but instead consider them to be a part ofthe final demand. This means that the environmental repercussions coming frominvestments in e.g. factories or power plants, are not included in the environmentalimpacts occurring along the supply chain due to the consumption of some product.For instance, when a final user is consuming electricity from the energy sector, theCO2 emissions occurring directly and indirectly due to the building of the nuclearpower plant which produces the electricity, are excluded. These questions areaddressed in open versus closed input–output models, and in the field of dynamicinput–output modelling, and will be suggested as an area for further research.86,87

Another issue with interest for resource use research, is so called supply-constrainedinput–output models.88 In normal models, the supply or the output is consideredto be a function of the final demand, x = f(y). In supply-constrained models,some parts of the output will be constrained, making the other parts of the outputbeing a function of the constrained parts. Hence, the output of the non-constrainedproducts is not only dependent on the final demand, but also on how much outputthe constrained products can deliver (in standard IO-models, there is no limit onhow much output the various products can deliver). This subject has been studiedfor instance with respect to peak oil.89

84See Weber and Matthews, 2007. MER versus PPP is also discussed in e.g. ITPS, 2008, andNordhaus, 2007, arguing for the PPP approach, and in Peters and Hertwich, 2009, arguing forthe MER approach.

85Also, a short examination of the uncertainties in connection with the aggregation problemwas done in an early stage of the study, but this will not be presented here.

86See Miller and Blair, 2009, although environmental considerations in connection with thisissue is not discussed there.

87Including investments in this way would also solve the problem of not properly allocatethe investments in the exports industry. These are now wrongly included in the domestic finaldemand.

88See Miller and Blair, 2009.89Kerschner and Hubacek, 2009.

Chapter 4

Study-specific data and methods

In the previous chapter, we went through the theoretical foundations for the meth-ods used in input–output analysis, and its environmental extension. In this chap-ter, we will describe the methods used in this specific study. This chapter assumesthat the theory explained in Chapter 3 is already known, accordingly we will hereonly describe the specifics for this study and not go into particulars about thetheory lying behind.

For detailed calculations and data, see the accompanying Excel database presentedin Appendix F.

4.1 Organization

Data and methods used can be organized into the following parts:

Economical data and methods:

� Collection and pretreatment of economical data from SUTs and IOTs.

� Generation of IOT time series using updating methods for years missingofficial IOTs.

� Calculation of the Leontief inverse and the required production to meet finaldemand.

Environmental data and methods:

� Collection of domestic environmental data

� Calculation of domestic intensities

� Calculation of world average intensities

42

Chapter 4 Study-specific data and methods 43

Master calculations:

� The master expression

� Physical trade balances

� IPAT and EKCs

� Decomposition analysis

� Sector analysis

� Analysis of final demand categories

4.2 Economical data and methods

4.2.1 Collection and pretreatment of economical data fromSUTs and IOTs

Supply tables, use tables and input–output tables are obtained from the Swedishnational accounts at Statistics Sweden.1 All these tables are available in two timeseries revisions, and both these revisions are parallelly used in the calculations:

� Revision 1993–2003 : For each year a supply table in basic prices and a usetable in market prices are obtained. IOTs are obtained for the year 1995and 2000. The IOTs are subdivided into a domestic table, an imports table,and a total table (domestic plus imports).

� Revision 2000–2005 : For each year a supply table in basic prices and a usetable in market prices are obtained. IOTs are obtained for the year 2000 and2005.2 The IOTs are subdivided into a domestic table, an imports table, anda total table (domestic plus imports).

The original tables provided by the national accounts, are in sizes of 55 x 55industries or products. Since the data from the environmental accounts are dividedinto 52 industries, all SUTs and IOTs are aggregated using an aggregation matrix,G, which means that certain industries or products are put together, yielding 52x 52 matrices, and vectors 52 elements long.3 For vectors, e.g. total output andfinal demand, the aggregation is performed through e.g.4

(4.1) xp = Gxp ,

1Statistics Sweden, 2011c, 2006a, 2009, 2006b, and 2008.2The IOT for 2000 from this latter time series revision, should not be confused with the IOT

for 2000 from the former time series revision.3The industries aggregated are shown in the accompanying Excel files, see Appendix F.4See Appendix C for details about aggregation operations.

44 Study-specific data and methods Chapter 4

meaning that some of the rows in xp are added and put together in xp. For themake and intermediate matrices the aggregation is done by e.g.

(4.2) S = GSG′ ,

meaning that some of the rows and their corresponding columns are added andput together in S to form S.

4.2.2 Generation of IOT time series using updating meth-ods for years missing official IOTs

Since the official IOTs are published every five years only, IOTs for the missingyears is calculated in the study. This is done beginning with a year where anofficial IOT in basic prices is available, e.g. year 2000, in order to use that year’sdivision of domestic production, imports, and taxes less subsidies. The followingsteps are then undertaken:

1. The intermediate matrix in the IOT in market prices for year 2000 is gener-ated from the SUTs from that year, through Fgen = US′c. The final demandmatrix y in the IOT in market prices for year 2000 is picked from the usetable for that year.5

2. The shares of domestic production, imports, and taxes less subsidies arecalculated for both the intermediate matrix of the IOT and the final demandtable of the IOT. For the intermediate matrix, this is done by6

F rd = Fd � Fgen ,(4.3)

F rm = Fm � Fgen ,(4.4)

and for the final demand matrix by

yrd = yd � y ,(4.5)

yrm = ym � y .(4.6)

3. For any year (here called the calculation year) that is using the official IOTfrom year 2000 (see step 5 below), a domestic and an imports IOT is gen-erated by firstly constructing an IOT in market prices (as in step 1 above),yielding Fgen and y (tilde above variables will here mean variables referring

to the calculation year). Then Fd, Fm, yd and ym are calculated by usingthe ratios calculated in step 2 above, yielding

Fd = F rd ⊗ Fgen ,(4.7)

Fm = F rm ⊗ Fgen ,(4.8)

yd = yrd ⊗ y ,(4.9)

ym = yrm ⊗ y .(4.10)

5Here y is considered a matrix, and not a vector as in all other calculations.6See Appendix C for definition of the element-wise multiplication and division operators ⊗

and �.


4. Finally, the calculated IOT for the calculation year, denoted by Fd, Fm,yd and ym are calibrated against the known sums of the real official xp

and m from the supply table from the calculation year. Since summing allthe elements of Fd and yd should yield the sum of xp (see the tables inAppendix E), but may not actually do this since they are generated fromthe official IOT which applies for another year, the ratio between the sumof xp to the sum of all elements in Fd and yd is calculated, and then all

elements in Fd and yd is multiplied by this ratio. This guarantees that thenew calibrated Fd and yd sums up to the real official sum of xp. The samereasoning goes for the imports part of the IOT.7

5. The official IOTs used for the various years in these calculations, are thefollowing:

(a) Revision 1993–2003: For the years 1993–1997 the IOT from 1995 isused. For the years 1998–2003, the IOT from 2000 is used.

(b) Revision 2000–2005: For the years 2000–2003 the IOT from 2000 isused. For the years 2004–2005, the IOT from 2005 is used.

4.2.3 Calculation of the Leontief inverse and the requiredproduction to meet final demand

The next step is to calculate the matrix of technical coefficients A. Two versionsare calculated, the domestic version Ad and the total version Atot = Ad + Am:

Ad = Fd x−1p ,(4.11)

Atot = (Fd + Fm)x−1p ,(4.12)

where Fd and Fm are the calibrated intermediate domestic and imports matricesfrom the calculated IOT for the current calculation year, and xp are the generatedand calibrated xp = Fd i + yd. The real official xp is not used, since it differselement-wise from the generated and calibrated one (even though their sums areequal), and this makes the calculations not completely consistent.

Based on that, the corresponding Leontief inverses are calculated as

Ld = (I −Ad)−1 ,(4.13)

Ltot = (I −Atot)−1 .(4.14)

Next, the total production – generated domestically and abroad due to domesticfinal demand (i.e. exclusive exports) of domestically produced products (ynexp

d ) andof products produced abroad (ynexp

m ) – is calculated as Ltotynexptot , where ynexp

tot =ynexpd + ynexp

m . That corresponds to the sum of the whole tree in Figure 3.2.The production generated domestically due to only domestic final demand (i.e.

7See Eurostat, 2008, for more advanced calibration procedures.


exclusive exports) of domestically produced products (ynexpd ) on the other hand,

is calculated as Ldynexpd . That corresponds to the sum of the nodes on the left

edge of the tree in Figure 3.2. And finally, the products produced abroad only– due to domestic final demand (i.e. exclusive exports) of domestically producedproducts and of products produced abroad – then becomes Ltoty

nexptot − Ldy

nexpd .

Note though, that feedback effects are not taken into account here, i.e. the shareof products produced abroad will probably be slightly too big since some of theimports have probably further back in the supply chain been produced in Swedenas exports. See also Chapter 3.3.1.

To summarize, required production produced in Sweden is

(4.15) Ldynexpd ,

and required production abroad is

(4.16) Ltotynexptot −Ldy

nexpd .

The domestic production caused by our exports is also interesting, and it can beexpressed as

(4.17) Ldyexpd ,

where yexpd is the exports part of the final demand of domestically produced prod-

ucts only (thus not including imports going to exports).

4.3 Environmental data and methods

4.3.1 Collection of domestic environmental data

Environmental pressure from industry, including bunkers

Environmental data are obtained from the environmental accounts from StatisticsSweden.8 The data comes from a newly revised time series (March, 2011) coveringthe period 1993–2005. Here the time series is pertaining to one revision only, i.e.the same methods are used throughout the whole time series.

The data include bunkers, i.e. resource use and emissions data due to internationalaviation and sea transports. This differs from the official UNFCCC data.9 Thus,even though these data from Statistics Sweden are purely production-based, theyare still higher than the official production-based UNFCCC data. Bunkers areused by both Swedish users and users from the rest of the world (e.g. domesticand foreign shipping companies), which may suggest Swedish users get allocated

8See Statistics Sweden, 2011d. For methods used by the environmental accounts to obtainthe data, see also Statistics Sweden, 2004, and Statistics Sweden, 2005.

9The reporting done by Sweden to UNFCCC, the United Nations Framework Convention onClimate Change. See Swedish EPA, 2011.


too much. However, since Swedish users also use bunkers in other parts of theworld and that use is not included in the calculations, it may even itself out. Inlack of data covering the allocation of bunker use between domestic and foreignusers in Sweden, this is the best method available.10

The energy resource part of the data from Statistics Sweden, refer to total finalconsumption of these resources, i.e. transformation losses during processing of theprimary energy source, is not included.11

For every year in the time series, these environmental data are organized in aresource use and emissions x industry matrix, Eind, where eindij refers to resourceuses or emissions of type i generated by the production in industryj. The resourceuses and emissions i are the following 15 variables:

� Energy resource use types : Aviation fuels, other petroleum products,fuel oil 1, fuel oil 2–5, engine petrol, diesel oil, solid fossils, and fossil gases(measured as TJ/year).

� Emissions: CO2, CH4, N2O, SO2, NOx, CO, and NMVOC (measured asMt/year).

Environmental pressure from direct use

In addition to these environmental data of resource use and emissions in the in-dustry (which will be used in the IOA calculations) the direct use of resource usesor emissions by final consumers need be added to the total calculations. Thesedata correspond to the environmental direct use box, in the right lower cornerof Figure 3.1. This is the resource uses or emissions occurring downstream afterconsumption during the usage phase, e.g. heating of housing and transports.

These data are obtained from the same data sets from the environmental accountsas the data above, but will for the analysis be organized into a separate vectoredir, where ediri refers to energy resource use or emission of type i. In realityedir is separated into columns denoting different consumer categories (non-profitorganizations’ use, public use, and private use), but here these columns are addedtogether and treated as one column.

Official data

For comparison, official production-based data corresponding to the environmentalvariables listed above, are obtained from Statistics Sweden (include bunkers),12 theSwedish energy authority (include bunkers),13 and from the Swedish reporting toUNFCCC (exclude bunkers).14

10Statistics Sweden, 2011b. See Cadarso et al., 2010, for a recent attempt to develop a newmethodology in this field.

11Statistics Sweden, 2011b.12Statistics Sweden, 2011d.13Swedish Energy Agency, 2010.14Swedish EPA, 2011.


4.3.2 Calculation of domestic intensities

Firstly, the matrix Eind need to be transformed to obtain the resource uses oremissions generated per product (see equation (3.3)). This is done by

(4.18) Ep = EindS′c ,

where epij refers to the resource use or emissions type i generated by product j.Thereafter the Swedish environmental intensity matrix Eswe

i is calculated by

(4.19) Eswei = Epx

−1p ,

where xp is the calibrated total production values for the various products over ayear (xp = Fd i + yd, Fd and yd obtained in the calibration procedure explainedin Chapter 4.2.2). Note that xp accordingly refers to gross output from the homo-geneous industries, and not the value added numbers. In Eswe

i the element ei,sweij

refers to the intensity of energy resource use or emission type i, in the productionof product j.

4.3.3 Calculation of world average intensities

World average intensities approach

In order to estimate the resource uses and emissions Swedish final demand causesabroad, world average intensities are used. The reason for this is that it is rea-sonable to believe that production occurring abroad is more resource use andemissions intensive than Swedish production, thus world average intensities yieldmore accurate estimates of resource use and emissions than Swedish intensitieswould provide.

It could be argued though, that the production abroad should be attributed inten-sities depending on where the production is imported from.15 Two problems existwith such an approach though. Firstly, in the Swedish statistics of imports, onlyinformation of the dispatching countries are shown, thus information about thecountry of origin where the products were produced and where the resource use oremissions took place, is not known.16 Investigations done in the 1990s suggestedmost of the dispatching countries where the same as the country of origin,17 butit is hard to know how much this has changed since then. Secondly, the productsproduced abroad to satisfy our final demand, are not only produced in the coun-tries we are importing from, but also in countries that our import countries intheir turn import from, and so on through the whole supply chain. It may be thata large portion of the indirect inputs come from other more resource and emissionsintensive countries.18,19

15This method is applied in Statistics Sweden, 2000, and in Swedish EPA and StatisticsSweden, 2008.

16Statistics Sweden, 2000, Swedish EPA, 2008, and Swedish EPA, 2010b.17Statistics Sweden, 2000.18Swedish EPA, 2008.19E.g. exports from China to Europe constitutes a considerable part of Europe’s CO2 emis-

sions, see Davis and Caldeira, 2010. See also Andersen et al., 2010, for transports from China.


Accordingly, intensities from our direct import countries may yield too low valuesof the emissions our final demand causes abroad. On the other hand world averageintensities may yield too high values, since these intensities are higher than typicalvalues from the European countries which we are importing from – somewherearound 20 % higher in 2005 for CO2.

20 But again, an unknown part of what weimport from European countries, may actually have been produced somewhereelse, so the true values may be somewhere in between. A more detailed analysisof these matters will be suggested for further research.

When it comes to the calculations of the world average intensities, the approachused in this study is to calculate the ratio between world intensities of resource usesor emissions per dollar GDP to Swedish intensities of resource uses or emissionsper dollar GDP, and then multiply this ratio with the Swedish environmental per-product intensities (see details below). The world intensities (e.g. emissions perGDP) can not be used directly, since the Swedish output resulting from the IOApart of the study, refers to gross output from the industries and not from the valueadded obtained in the industries.

Data

All GDP data is obtained from the World Bank.21 Swedish GDP and WorldGDP are used, covering the whole period 1993–2005. Two different GDP timeseries with different calculation methods are used. One uses the purchasing powerparity (PPP) method in constant 2005 international dollars – this is the time serieswe mainly will use. The other time series uses market exchange rates (MER) inconstant 2000 US dollars – this time series will be used as a comparison only.

The reason for using the PPP approach, is that the allocation of Swedish-inducedemissions abroad will be estimated too high with the MER-based GDP, due tothe fact that MER-based GDP underestimates the output produced in the world(when GDP is underestimated, the numerator in the ratio used to calculate theworld average intensity, will be too high).22 Some argue that the MER approachshould still be used, since products traded over borders are in fact valued MER.23

However, in this present study the argument is that the exports from the ROWreceives a too big share of the output from the ROW when the output of the ROWis valued at MER, since the output from the ROW, going both to exports and todomestic use, is really higher according to the PPP approach. Thus, the exports’(from the ROW) share in the responsibility for producing emissions there, is notas high.

World energy resource use data is obtained from IEA, with a time series coveringthe whole period used in this study (1993–2005).24 The variables used from the

20Based on Statistics Sweden, 2011g, and World Bank, 2010.21World Bank, 2010.22ITPS, 2008, has the same reasoning.23E.g. Weber and Matthews, 2007, and Peters and Hertwich, 2009. Nordhaus, 2007, gives a

contrary view.24IEA, 2010.


IEA database are oil, coal and gas. Note that these data refer to total finalconsumption of energy, and not to total primary energy demand. The reasonfor this is that the Swedish data refer to total final consumption of energy, i.e.transformation losses when converting energy resources to the kind of energy used,are excluded.

World emissions data is obtained from the EDGAR database, newly revised tocover time series up to the year 2005.25 The variables used from the EDGARdatabase is CO2, CH4, N2O, SO2, NOx, CO, and NMVOC.

World energy resource use and emissions data are assembled into the vector eworld.

All Swedish energy resource uses and emissions data used in the world average in-tensities calculations are obtained from the Swedish environmental accounts as inthe calculations of the domestic intensities above. The data used are the sums ofthe energy resource uses and emissions in both industry and as direct use, assem-bled into the vector eswe = Epi+ edir. It could be argued that the environmentaldata for Sweden ought to be obtained from the same sources as the environmentaldata from the world above. However, the environmental data for Sweden fromthese sources were found to differ too much from the Swedish environmental ac-counts data, and it is reasonable to believe that Swedish environmental accountsdata are more reliable.

Calculations

Two vectors, kPPP and kMER are compiled describing the ratio of world intensityto Swedish intensity. For the PPP case, each cell in these vectors are calculatedas

(4.20) kPPPi =

eworldi /GDPworld

PPP

eswei /GDP swe

PPP

where kPPPi refers to the world–Sweden intensity ratio for the resource use or

emission type i, eworldi (which comes from the vector eworld defined above) refers to

the total amount of that resource use or emission type i generated during a yearfor the world, and eswe

i (which comes from the vector eswe defined above) refers tothe total amount of that resource use or emission type i generated during a yearfor Sweden. Since eworld are obtained in a more aggregate version than eswe (ineswe there are for instance six categories of oil, and in eworld there are just onecategory of oil), some of the elements in eswe are added together before the cellsin kPPP are calculated.26

Finally, to obtain the world average intensities, every column in the matrix Eswei

are multiplied element-wise with column vector kPPP to obtain the matrix EPPPi ,

which is done by first diagonalizing kPPP to kPPP and then do

(4.21) EPPPi = kPPPE

swei .

The corresponding calculations are carried out to obtain EMERi .

25EDGAR, 2010. This database is used by WRI among others, see WRI, 2011.26See the accompanying Excel database for details (Appendix F).


4.4 Master calculations

4.4.1 The master expression

At this stage, we put all previous calculations together, to produce the mainresults. The master expression then obtained can be expressed as

(4.22) Environmental pressure = Domestic + Abroad + Direct use .

Domestic means all resource uses or emissions generated in Sweden due to Swedishfinal demand of domestic products. Abroad means resource uses or emissions gen-erated abroad due to Swedish final demand of domestic products and of prod-ucts produced abroad. Direct use means resource uses or emissions generated bySwedish final consumers in the usage phase of products (e.g. heating, transports).

More formally, the master expression is expressed as

(4.23) etot = G (EiLdynexpd + kEi(Ltoty

nexptot −Ldy

nexpd ) + edir ) ,

and this calculation is performed for every year in the two time series revisions1993–2003, and 2000–2005.

The aggregation matrix G is used to aggregate the various environmental parame-ters listed in Chapter 4.3.1, yielding the aggregated vector etot which now containsthe following environmental parameters:27

� Energy resource uses types : Oil, coal, gas and total fossil fuel use (measuredas TWh/year).

� Emissions: CO2, CH4, N2O, CO2eq, SO2, NOx, CO, and NMVOC (measuredas Mt/year).

In the vector etot, etoti refers accordingly to the resource use or emission of type

i generated totally upstream through the whole supply chain, and downstreamincluding the usage phase and the disposal phase.28 The world–Sweden intensityratio k is diagonalized to k in order to be able to multiply it with the resourceuse or emissions-based Swedish intensities.

Some variations of equation (4.23) are calculated. With k as kPPP or kMER the en-vironmental load based on PPP-based GDP or MER-based GDP are determined.With k = I the environmental load based on Swedish intensities for productionabroad, are determined.

27See the accompanying Excel database (Appendix F), too see the exact structure of G. ForCO2eq, the following weights are used: 1 for CO2, 21 for CH4 and 310 for N2O. See Fuglestvedtet al., 2003. A similar aggregation approach for constructing CO2eq is used in Lenzen, 1998.

28The disposal phase is included to that extent that waste services are a part of the industry.


4.4.2 Physical trade balances

The resource use and emissions caused by exports are calculated as

(4.24) eexp = GEiLdyexpd ,

where yexpd is the exports part of the final demand of domestically produced prod-

ucts (imports going to exports not included). Based on this result and the middleterm in equation (4.23), a physical trade balance for resource uses or emissions iscalculated as

(4.25) G (EiLdyexpd − kPPPEi(Ltoty

nexptot −Ldy

nexpd )) .

4.4.3 Decomposition analysis

Equation (4.23) is in itself decomposed into three terms. However, it is also pos-sible to decompose the middle term into the contribution from k and the contri-bution from the rest of that term, in order to analyse how much of the change inenvironmental pressure abroad is caused by the change in the intensities abroad,or by the change in impact abroad if Swedish intensities applied.

Analysing a certain environmental variable ei,29 we have equation (4.23) as

(4.26) ei = eiiLdy

nexpd + kie

ii(Ltoty

nexptot −Ldy

nexpd ) + ediri ,

where eii is a row vector with intensities for the environmental variable i, and ediri

is the sum of direct use of resource uses or emissions for the environmental variablei.

Now, if we denote the right side of the middle term in equation (4.26) asmi=ei

i(Ltotynexptot − Ldy

nexpd ) – thus the middle term becomes equal to kimi –

we can decompose the middle term into f(∆ki) + g(∆mi), to see the effects ofchanging ki and the effects of changing mi. We also denote the leftmost term asedi = ei

iLdynexpd , in order to make the following equation easier to read. Relying

on the results in equation (3.21) and (3.22), the decomposition of equation (4.26)then becomes

(4.27) 100 · ∆eie0i

= 100 · ∆edie0i

+ 100 · f(∆ki)

e0i+ 100 · g(∆mi)

e0i+ 100 · ∆ediri

e0i,

and the components f(∆ki) and g(∆mi) are

f(∆ki) =1

2(m0

i ∆ki + m1i ∆ki) ,(4.28)

g(∆mi) =1

2(k0

i ∆mi + k1i ∆mi) .(4.29)

To obtain a decomposition diagram of equation (4.27), the “deltas” are changedconsecutively from the base year up to the end year of the time series.

29Index tot and tilde stripped from etoti for making it easier to read.


4.4.4 IPAT and consumption–environmental impact rela-tionships

IPAT diagrams and consumption–environmental impact diagrams are also gener-ated in order to see if any decoupling or EKC patterns can be detected. For acertain resource use or emission type i in etot from equation (4.23), the IPAT isformed as30

(4.30) 100 · eti

e0i= 100 · P

t

P 0× 100 · (C/P )t

(C/P )0× 100 · (ei/C)t

(ei/C)0,

where t runs over all years studied, and 0 indicates base year, P is population, Cis final demand less exports in constant prices.31 Note that C is used, not ynexp

tot ,since the latter is not in constant prices.

Consumption–environmental impact diagrams are generated by plotting ei againstfinal demand less exports per capita in constant prices. The Swedish values inconstant prices are converted to dollars using a fixed exchange rate from 2005.32

4.4.5 Product groups analysis

The effect of the final demand of specific product groups for certain sectors isdone by applying equation (4.23) and in ynexp

d and ynexptot cancel all elements out

except for the ones which product groups are to be analysed. The use of edir isnot relevant here, since edir doesn’t belong to any product group.

4.4.6 Analysis of final demand categories

The environmental pressure caused by various categories of final demand (i.e.households, public sector, investments and exports), is obtained by applying equa-tion (4.23), but using yd and ytot rather than ynexp

d and ynexptot . Furthermore, in

yd and ytot all columns are removed except for the column which final demandcategory is to be analysed (thus yd and ytot are considered matrices with severalcolumns which represent the various categories of final demand – in all other cal-culations, the final demand vector is considered to be the sum of all final demandcategory columns). The use of edir is excluded in these calculations.

30Index tot and tilde stripped from etoti for making it easier to read.31Population data and consumption data in constant prices from Statistics Sweden, 2011e,

and Statistics Sweden, 2011f.32World Bank, 2010.

Chapter 5

Results

In the previous chapter we went through the detailed methods used in this study.In this chapter we will present the results generated by those methods. The resultsare organized into the following sections:

� Time series of environmental impact in domestic, abroad, and direct usecomponents. Diagrams for all energy use and emission variables studied.

� Decomposition analysis for oil use, and for CO2, CH4 and SO2 emissions.

� IPAT-diagrams for fossil fuel use, and for CO2, CH4 and SO2 emissions.

� Diagrams for analysing consumption–environmental impact relationships(decoupling and EKC patterns), for fossil fuel use, and for CO2, CH4 andSO2 emissions.

� Product groups analysis for fossil fuels, and for CO2 equivalents. This meansanalysing how the consumption of various product groups affect the envi-ronment.

� Emissions of CO2 equivalents distributed over the categories of final demand.

In some instances above where analysis is not done on all environmental variables,a more comprehensive results table is available in Appendix G. For all results, seethe accompanying Excel database (introduced in Appendix F).

Sources for production-based data in the diagrams, and indications whether theseinclude bunkers or not, are given in the figure captions. For sources and meth-ods concerning consumption-based data in the diagrams, see Chapter 4. Allconsumption-based data are based on environmental accounts data which includethe use of bunkers. All consumption-based results including resource use and emis-sions abroad are based on the PPP assumption, if not otherwise indicated – seeChapter 4.3.3 for details.

54

Chapter 5 Results 55

5.1 Environmental impact from production in

Sweden and abroad, and from direct use

In Figure 5.1–5.3, the consumption-based environmental impact is presented forall the environmental variables analysed in the study. The diagrams in thesefigures correspond to equation (4.22) and (4.23) in Chapter 4.4.1. That is, totalconsumption-based environmental impact is divided into domestic impact (due todomestic final demand of domestic products), impact abroad (due to domestic finaldemand of domestic and imported products), and impact in direct use (impact dueto e.g. heating of housing and transports by final consumers). Production-baseddata are included in the diagrams as a comparison.

Data for total consumption-based impact, domestic impact, and impact abroad,come in two time series revisions – 1993–2003 and 2000–2005 – and for that reasonthese curves are shown doubled for the years 2000–2003.

For energy uses (Figure 5.1), direct use seems to be declining a little bit, while usecaused abroad is increasing slightly, resulting in a neither decreasing or increasingtrend in total consumption-based energy use.

1990 1995 2000 2005 20100

50

100

150

200

250

Production-based

Consumption-based, total

Oil use, 1993-2005

Year

Oil u

se [T

Wh

per y

ear]

Direct useDomestic

Abroad

1990 1995 2000 2005 20100

10

20

30

40

Production-based


DomesticDirect use

Abroad

Year

Coal

use

[TW

h pe

r yea

r]

Coal use, 1993-2005

1990 1995 2000 2005 20100

10

20

30

40

50

Production-based


Domestic

Direct use

Abroad

Year

Gas

use

[TW

h pe

r yea

r]

Gas use, 1993-2005

1990 1995 2000 2005 20100

50

100

150

200

250

Production-based


Domestic

Direct use

Abroad

Year

Foss

il fu

el u

se [T

Wh

per y

ear]

Fossil fuel use, 1993-2005

Figure 5.1. Consumption-based time series of oil use, coal use, gas use, and fossil fueluse. Source: Production-based data from Statistics Sweden, 2011d (including bunkers).

56 Results Chapter 5

For the greenhouse gases (Figure 5.2), an increasing trend for the consumption-based data is detectable, going contrary to the emissions from the production-based UNFCCC data. This is most evident in the case of CH4, which probably isexplained by a strong increase in net imports of food and agricultural products.1

In the aggregate, emissions of CO2eq increased approximately 20 % in the period.

For SO2 and NOx (Figure 5.3), the emissions are declining in the first time series,but in the second time series they come at a higher level, and are possibly on therise. The reason for this large discrepancy between the time series seems to bedue to a large reclassification in the new time series revision of exports of shippingservices (i.e. sea transports), with a decrease of about 20 %. Since exports andall their indirect effects are deducted from the calculations, emissions caused bydomestic final demand will then increase, especially since the shipping industry isvery emissions intensive.2

For CO and NMVOC (Figure 5.3), emissions decline. At the same time, however,the component of emissions abroad increase.

1990 1995 2000 2005 20100

25

50

75

100

Production- based


Domestic

Direct use

Abroad

Year

CO

2 emissio

ns [M

t per

yea

r]

CO2 emissions, 1993-2005

1990 1995 2000 2005 20100

0.25

0.5

0.75

1

1.25

1.5

Production- based


DomesticDirect use

Abroad

Year

CH

4 emissio

ns [M

t per

yea

r]

CH4 emissions, 1993-2005

1990 1995 2000 2005 20100

10

20

30

40

50

60

Production- based


DomesticDirect use

Abroad

Year

N 2O emiss

ions

[kt p

er y

ear]

N2O emissions, 1993-2005

1990 1995 2000 2005 20100

25

50

75

100

125

150

Production- based


Domestic

Direct use

Abroad

Year

CO

2eq emiss

ions

[Mt p

er y

ear]

CO2eq emissions, 1993-2005

Figure 5.2. Consumption-based time series of greenhouse gas emissions. Source:Production-based data from Swedish EPA, 2011 (UNFCCC; excluding bunkers).

1Increased by more than 30 % in the period 2000–2005 – see Statistics Sweden and SwedishBoard of Agriculture, 2006.

2Confirmed by Statistics Sweden, 2011b. Also, the data in the new time series revision areconsidered to have higher quality according to Statistics Sweden, 2011a.


Table 5.1 shows data for fossil fuel use and CO2 equivalents, with consumption-based data based on three different assumptions: the PPP assumption, the MERassumption, and the assumption of Swedish intensities for production abroad (seeChapter 4.3.3 for details about these assumptions). Using the assumption ofSwedish intensities yields similar values as the official production-based data. Us-ing the MER assumption yields even higher values than the PPP assumption. Theintensity ratio refers to the ratio between world intensities and Swedish intensities.

The physical trade balances refer to the net exports of fuel use or emissions. Apositive value means that the energy use or emissions occurring on the Swedishterritory due to the consumption abroad of Swedish products, are higher than theenergy use or emissions occurring abroad due to Swedish final demand. Negativevalues mean that the energy use or emissions occurring abroad due to our finaldemand are higher than the energy use or emissions occurring in Sweden due toour exports. The physical trade balances for fossil fuel use and CO2 equivalentsshow negative values, and in particular for CO2 equivalents these negative valuesare growing (i.e. growing even more negative).

1990 1995 2000 2005 20100

50

100

150

200

250

300

Production- based


Direct use

Abroad

Year

SO

2 emissio

ns [k

t per

yea

r]

SO2 emissions, 1993-2005

Domestic

1990 1995 2000 2005 20100

50

100

150

200

250

300

350

400

Production- based


DomesticDirect use

Abroad

Year

NO

x emissio

ns [k

t per

yea

r]

NOx emissions, 1993-2005

1990 1995 2000 2005 20100

0.25

0.5

0.75

1

1.25

1.5

Production- based


DomesticDirect use

Abroad

Year

CO e

miss

ions

[Mt p

er y

ear]

CO emissions, 1993-2005

1990 1995 2000 2005 20100

50

100

150

200

250

300

350

400

Production- based


Domestic

Direct useAbroad

Year

NMVO

C em

issio

ns [k

t per

yea

r]

NMVOC emissions, 1993-2005

Figure 5.3. Consumption-based time series of SO2, NOx, CO and NMVOC emissions.Source: Production-based data from Swedish EPA, 2011 (UNFCCC; excluding bunkers).

58R

esults

Chap

ter5

Table 5.1. Consumption-based and production-based data, and physical trade balance, for fossil fuel use and CO2 equivalents. Cons.(PPP) refers to the PPP assumption; analogous for the other similar row captions. Source: Production-based data from Statistics Sweden,2011d (fossil fuel use, including bunkers) and from Swedish EPA, 2011 (UNFCCC; CO2eq emissions, excluding bunkers).

Variable \ Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2000 2001 2002 2003 2004 2005

Economy

Population (1000s) 8719 8781 8827 8841 8846 8851 8858 8872 8896 8925 8958 8872 8896 8925 8958 8994 9030

Dom. FD/cap ($/year) 28807 29675 30293 30603 31205 32683 33921 35281 35261 35705 36287 35281 35261 35705 36287 36916 37845

Fossil fuels (TWh/year)

Cons. (PPP) 212 219 216 221 209 212 207 206 200 203 205 210 206 209 213 222 219

Cons. (MER) 237 246 244 249 237 240 236 238 231 235 237 244 239 243 249 265 264

Cons. (swe. int.) 188 195 189 198 182 189 180 174 172 174 177 178 177 180 185 188 180

Int. ratio (PPP) 1.58 1.53 1.61 1.51 1.60 1.52 1.61 1.70 1.63 1.63 1.61 1.66 1.59 1.60 1.56 1.59 1.66

Phys. trade balance -7.78 -4.58 -4.54 4.15 2.65 4.39 -0.77 -4.76 2.37 0.47 6.44 -9.38 -3.93 -6.38 -2.52 -10.47 -13.82

Production-based 204 215 211 226 211 217 206 201 203 203 211 201 203 203 211 212 205

CO2eq (Mt/year)

Cons. (PPP) 103 105 105 103 100 106 106 106 105 108 108 107 107 110 111 122 123

Cons. (MER) 122 125 126 123 120 128 129 131 130 134 135 132 133 137 139 156 159

Cons. (swe. int.) 75 76 74 75 70 74 71 69 68 69 70 70 70 71 72 75 72

Int. ratio (PPP) 2.36 2.31 2.41 2.30 2.40 2.42 2.55 2.61 2.62 2.69 2.66 2.59 2.60 2.67 2.63 2.70 2.83

Phys. trade balance -27 -26 -26 -21 -21 -26 -29 -32 -30 -33 -31 -33 -32 -35 -34 -43 -47

Production-based 72 75 74 77 73 73 70 68 69 69 70 68 69 69 70 69 66


5.2 Decomposition analysis

In order to determine the various components contributing to the change in en-vironmental pressure, an additive index decomposition analysis has been under-taken. In Figure 5.4, the results for the period 2000–2005, for oil use, and forCO2, CH4 and SO2 emissions, are shown. The results for the other variables, andfor the period 1993–2003 are available in the accompanying Excel database – seeAppendix F.

The decomposition analysis involves the examination of how much the variouscomponents analysed contribute to the total percentage change in energy use oremissions in the period. Here, the components in the diagrams are domestic energyuse or emissions caused by Swedish final demand for domestic products, energy useor emissions abroad if Swedish intensities applied, intensity ratio between worldintensity and Swedish intensity, and energy use or emissions in direct use.

The decomposition of environmental pressure abroad into an intensity ratio com-ponent (i.e. ratio between world and Swedish intensity) and a “neutral” abroadcomponent, entails the possibility to analyse how much the change in pressureabroad is caused by changing world intensities in relation to Swedish intensities,

1999 2000 2001 2002 2003 2004 2005 2006-10

-8

-6

-4

-2

0

2

4

6

8

10 Decomposition of changein oil use, 2000-2005

Intensity ratio

Total changeDomestic

Direct use

Abroad

Year

Chan

ge in

oil

use

[%]

1999 2000 2001 2002 2003 2004 2005 2006-15

-10

-5

0

5

10

15

Year

Chan

ge in

CO 2 emis

sions

[%]

Decomposition of change in CO2emissions, 2000-2005

Total change

Domestic

Intensity ratio

Abroad

Direct use

1999 2000 2001 2002 2003 2004 2005 2006-20

-15

-10

-5

0

5

10

15

20

25

30

35

Year

Chan

ge in

CH 4 emis

sions

[%]

Decomposition of change in CH4 emissions, 2000-2005

Total change

Domestic

Intensity ratio

Abroad

Direct use

1999 2000 2001 2002 2003 2004 2005 2006-20

-15

-10

-5

0

5

10

15

20

25

30

35

Year

Chan

ge in

SO 2 emis

sions

[%]

Decomposition of change in SO2emissions, 2000-2005

Total change

Domestic

Intensity ratio

Abroad

Direct use

Figure 5.4. Decomposition analysis of change in oil use, and in CO2, CH4 and SO2

emissions, in the period 2000–2005.


or by changing impact abroad due to Swedish final demand when Swedish inten-sities apply. See Chapter 4.4.3 for details regarding the calculations used in thisdecomposition analysis.

As have been noted earlier, the decline in direct use for oil use is counteracted bythe energy use or emissions caused by our demand for foreign produced productsand their inputs through the supply chain abroad. For CO2 most of the changecomes from higher levels of emissions from products produced abroad, and to someextent, worsened emission intensities of the world relative the intensities of Sweden.The same applies to CH4 in an even higher degree. For SO2 total emissions rise,even though the component of intensity ratio between the world intensity and theintensity of Sweden declines.

5.3 IPAT diagrams

In Figure 5.5, IPAT diagrams for fossil fuel use, and CO2, CH4 and SO2 emissionsare presented for the period 2000–2005. For reasons easy to understand in the

2000 2001 2002 2003 2004 200590

95

100

105

110

Year

Inde

x (2

000=

100)

IPAT diagram, fossil fuel use, 2000-2005

Total change, consumption-based

Population

Cons./cap

Fossil fuel use/unit of cons.

Total change, production-based

2000 2001 2002 2003 2004 200595

100

105

110

115

Year

Inde

x (2

000=

100)

IPAT diagram, CO2 emissions, 2000-2005


Population

Cons./cap

CO2 emissions/unit of cons.


2000 2001 2002 2003 2004 200590

95

100

105

110

115

120

125

130

Year

Inde

x (2

000=

100)

IPAT diagram, CH4 emissions, 2000-2005


Population

Cons./cap

CH4 emissions/unit of cons.


2000 2001 2002 2003 2004 200580

85

90

95

100

105

110

115

120

Year

Inde

x (2

000=

100)

IPAT diagram, SO2 emissions, 2000-2005


Population

Cons./capSO2 emissions/unit of cons.


Figure 5.5. Consumption-based IPAT diagrams for fossil fuel use, and for CO2, CH4

and SO2 emissions in the period 2000–2005. Source: Production-based data from Statis-tics Sweden, 2011d (fossil fuel use, including bunkers) and from Swedish EPA, 2011(UNFCCC; CO2, CH4 and SO2 emissions, excluding bunkers).


case of Sweden, the population factor does not contribute in a crucial way. Theaffluence factor – consumption per capita, or more correctly, Swedish final demandper capita – contributes in a more evident way. The technology factor – i.e. theintensity – contributes more or less for the emissions shown in the figure, but forfossil fule use, this factor counteracts the other in some extent.

Results for the other environmental variables and for the period 1993–2003, areavailable in the accompanying Excel database – see Appendix F.

5.4 Consumption–environmental impact diagrams

concerning decoupling and EKC patterns

In Figure 5.6, consumption-based environmental impact against Swedish final de-mand regarding fossil fuel use, and CO2, CH4 and SO2 emissions are shown. Dur-ing the period from 1993–2005, Swedish final demand grew from approximately28 000 constant US dollars, to 38 000 constant US dollars. At the same time,

27 500 30 000 32 500 35 000 37 500 40 000150

175

200

225

250

Consumption-based

Domestic final demand/cap [const. 2005 US $]

Foss

il fu

el u

se [T

Wh

per y

ear]

Fossil fuel use vs dom. final demand

Production-based

27 500 30 000 32 500 35 000 37 500 40 0000

25

50

75

100

Production- based

Consumption-based


CO

2 emissio

ns [M

t per

yea

r]

CO2 emissions vs dom. final demand

27 500 30 000 32 500 35 000 37 500 40 0000

0.25

0.5

0.75

1

1.25

1.5

Consumption-based


CH

4 emissio

ns [M

t per

yea

r]

CH4 emissions vs dom. final demand

Production- based

27 500 30 000 32 500 35 000 37 500 40 0000

50

100

150

200

250

300

Production- based

Consumption-based


SO

2 emissio

ns [k

t per

yea

r]

SO2 emissions vs dom. final demand

Figure 5.6. Consumption-based environmental impact versus domestic final demandfor fossil fuel use, and for CO2, CH4 and SO2 emissions. Source: Production-based datafrom Statistics Sweden, 2011d (fossil fuel use, including bunkers) and from Swedish EPA,2011 (UNFCCC; CO2, CH4 and SO2 emissions, excluding bunkers).


fossil fuel use remained at approximately the same level. However, CO2 emis-sions and especially CH4 emissions rose with rising domestic final demand. Thatsuggests that when looking from a consumption perspective, there is no EKC pat-tern for these emissions and decoupling has not occurred – contrary to what theproduction-based data indicate. Moreover, these emissions are much higher thantheir production-based analogs.

Regarding SO2 emissions, they decline in the first time series and accordingly havedecoupled there, but the opposite applies to the second time series (see Chapter5.1 for an explanation of this). Both time series though, show a higher level thanthe official production-based data.

The doubling of the consumption-based curves, is due to the fact that the two timeseries revisions of the Swedish national accounts were used, resulting in duplicatevalues for the period 2000–2003.

The other environmental variables are available in the accompanying Excel database– see Appendix F.

5.5 Environmental impact per product group

In Figure 5.7, the fossil fuel use and the emissions of CO2 equivalents due tothe consumption of goods or the consumption of services less transports,3 areshown for the period 2000–2005 and compared to the production-based data forthese product groups. In Table 5.2, a more comprehensive list of product groupsare shown, and their consumption-based and production-based emissions of CO2

equivalents respectively. In the accompanying Excel database, results for the otherenvironmental variables are available – see Appendix F.

2000 2001 2002 2003 2004 20050

25

50

75

100

125

Year

Foss

il fu

el u

se [T

Wh

per y

ear]

Fossil fuel use, goods vsservices excl. transports

Goods, consumption-based

Goods, production-based

Services excl. transp., consumption-based

Services excl. transp., production-based

2000 2001 2002 2003 2004 20050

25

50

75

100

Year

CO

2eq emiss

ions

[Mt p

er y

ear]

CO2eq emissions, goods vs services excl. transports

Goods, consumption-based

Goods, production-based

Services excl. transp., consumption-based

Services excl. transp., production-based

Figure 5.7. Fossil fuel use and emissions of CO2 equivalents in 2000–2005, for goodsand for services less transports in the production-based case and in the consumption-based case. Source: Production-based data Statistics Sweden, 2011d (incl. bunkers).

3Transports have been deducted from services in order to include only low environmentalimpact activities, which is what is normally associated with services.

Chap

ter5

Resu

lts63

Table 5.2. Consumption-based and production-based emissions of CO2 equivalents, per various product groups.Source: Production-based data from Statistics Sweden, 2011d (including bunkers).

Product group \ Year 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2000 2001 2002 2003 2004 2005

CO2eq (Mt/year), consumption-based

Goods 52.85 54.13 54.34 52.64 49.90 56.09 55.53 56.17 56.17 59.02 59.99 55.17 55.82 59.06 60.16 66.78 67.57

Services 30.96 31.94 31.44 31.61 31.87 32.61 33.04 33.15 33.09 33.16 32.92 35.14 35.49 35.31 35.79 40.00 41.07

Services, excl. transp. 27.03 27.69 27.23 27.35 27.38 28.07 28.14 28.25 27.86 28.13 28.08 29.04 29.15 29.21 29.50 32.10 33.47

Food 18.03 18.59 17.46 17.05 16.75 18.07 17.65 17.07 16.29 16.43 16.36 15.42 14.81 15.28 15.38 18.69 19.32

Steal and metal -0.20 0.05 0.17 -0.21 0.17 -0.15 -0.12 0.29 -0.06 0.11 -0.17 0.27 -0.30 0.10 -0.18 -1.14 -0.22

Energy 5.68 6.00 5.55 7.19 5.62 5.99 5.20 4.12 4.99 5.58 6.36 3.99 4.86 5.48 6.25 5.96 4.83

Transports 3.93 4.25 4.20 4.26 4.49 4.54 4.90 4.91 5.24 5.03 4.85 6.10 6.33 6.11 6.29 7.89 7.60

Education, healthcare 5.99 6.06 5.87 5.67 5.49 5.78 5.59 5.44 5.72 6.10 6.10 5.52 6.17 6.24 6.24 6.73 6.74

Culture, sports 1.06 1.12 1.12 1.16 1.11 1.15 1.15 1.11 1.06 1.07 1.06 1.27 1.24 1.27 1.32 1.47 1.55

CO2eq (Mt/year), production-based

Goods 42.04 44.29 43.69 47.68 43.42 44.32 41.13 40.10 41.68 42.67 43.74 40.10 41.68 42.67 43.74 43.58 42.08

Services 14.91 15.94 15.69 15.85 16.89 17.99 18.14 17.71 17.62 16.74 18.34 17.71 17.62 16.74 18.34 19.79 20.03

Services, excl. transp. 6.25 6.25 6.04 6.11 6.10 6.09 6.08 5.97 6.14 5.96 6.02 5.97 6.14 5.96 6.02 6.10 6.05

Food 1.05 1.08 1.09 1.11 1.13 1.13 1.11 0.98 0.87 0.92 1.02 0.98 0.87 0.92 1.02 0.83 0.75

Steal and metal 5.11 5.51 5.87 5.71 5.72 5.69 5.91 6.14 6.18 6.34 6.16 6.14 6.18 6.34 6.16 6.42 6.12

Energy 10.02 10.67 9.76 13.18 10.02 10.67 8.75 6.83 7.98 9.04 10.54 6.83 7.98 9.04 10.54 10.28 8.97

Transports 8.67 9.69 9.65 9.75 10.79 11.90 12.06 11.74 11.49 10.78 12.32 11.74 11.49 10.78 12.32 13.70 13.98

Education, healthcare 0.13 0.14 0.13 0.13 0.13 0.14 0.14 0.15 0.16 0.15 0.15 0.15 0.16 0.15 0.15 0.15 0.14

Culture, sports 0.06 0.06 0.06 0.06 0.06 0.07 0.07 0.07 0.08 0.09 0.09 0.07 0.08 0.09 0.09 0.09 0.10


It can be noted that the consumption-based emissions for various services are at amuch higher level than their corresponding production-based counterparts, whichshows that services, indirectly through the supply chain, depend on more resourceand emissions intensive sectors.

5.6 Environmental impact per final demand cat-

egory

Figure 5.8 shows consumption-based emissions of CO2 equivalents per final de-mand category in 1993–2005. For e.g. households, all emissions occurring in Swe-den and abroad due to the Swedish households’ consumption are included. Notethough that emissions due to direct use are not included – these data only refer tothe emissions caused upstream through the supply chain by the purchases thesefinal demand categories make. The doubling of the curves in 2000–2003 is due tothe use of the two time series revisions from the Swedish national accounts.

The public sector and the investments sector show almost no variation in theperiod. The households sector however, show a quite strong increase from approx-imately 55 Mt CO2eq per year in the beginning of the period to almost 75 MtCO2eq per year in the end of the period.

Exports, which are deducted from the other calculations in this study, are hereincluded as one of the final demand categories to show its rising environmentalimpact – the emissions almost double in the period, from approximately 50 MtCO2eq per year to almost 95 Mt CO2eq per year. Note though that these emis-sions include also emissions abroad due to the inputs from abroad required by theSwedish exports industry.

Results for the other environmental variables are available in the accompanyingExcel database – see Appendix F.

1990 1995 2000 2005 20100

25

50

75

100CO2eq emissions, for various final demand categories

Public

Investments

Year

CO

2eq emiss

ions

[Mt p

er y

ear]

Households

Exports

Figure 5.8. Consumption-based emissions of CO2 equivalents in 1993–2005, distributedover the various categories of final demand.

Chapter 6

Discussion and conclusions

The purpose of this study has been to contribute to the understanding of whethereconomic growth is the main cause to the world’s environmental problems. Ina world where we have already passed many of the ecological limits, and whereresource depletion and climate change are some of the biggest challenges facinghumankind,1 many are of the opinion that it is not possible to grow our economiesfor ever. Others say that growing the economy is a prerequisite for being able todevelop new technologies which will solve the environmental problems. Referringto the IPAT equation, this means to increase the A factor in order to decrease theT factor even more, so that the A factor – and obviously the P factor as well –doesn’t eat up the gains done by the T factor. In plain language, efficiency gainsneed to be bigger than increases in scale.

When analysing whether it is possible to grow a particular country’s economyand at the same time decrease its environmental impact – which is also whatthe environmental Kuznets curve (EKC) hypothesis suggests – we have to getan accurate description of what environmental impact the economy really causes.That is, we have to consider not only the domestic environmental impact but alsothe worldwide environmental impact caused by the consumption in the economy.Considering only the domestic environmental impact – as is normally done in EKCstudies – is simply not telling the whole picture. That is the reason why EKCstudies and studies measuring individual countries’ environmental performanceneed analyse the impact from a consumption perspective which includes the impactcaused abroad.2

In order to get an indication whether or not economic growth and increased con-sumption is compatible with decreasing environmental impact, we have in thisstudy analysed the worldwide, consumption-based environmental impact causedby the Swedish domestic final demand. This has been done by estimating theconsumption-based development of twelve environmental variables for the period1993–2005, using environmental input–output analysis.

1See Rockstrom et al., 2009, for a recent overview of the environmental state of the world.2E.g. Carson, 2010, Rothman, 1998, and Arrow et al., 1995.

65

66 Discussion and conclusions Chapter 6

6.1 Summary of main results and outcomes

Below follows an overview of the main results obtained from the analysis. Includedin this overview are also methodological attainments and other outcomes thatthis study has produced. After that, in the next sections, follows a discussionregarding the reliability of these results, and the results in comparison to otherstudies. Conclusions and suggestions for further research end the chapter.

� Methodological results:

– The wider conclusion that environmental impact be analysed from aconsumption perspective to supplement the production-based data pri-marily published today. This has important policy implications, e.g. inclimate change negotiations.

– The development of a new method for updating input–output tableswhich utilizes the shares of domestic production and imports from theofficial tables, and calibrates against known yearly domestic productionand imports totals (see Chapter 4.2.2).

– The deployment of a single-regional input–output model augmentedwith world average intensities (see Chapter 4.3.3).

– An index decomposition analysis which separates the change in impactinto components describing changes in domestic production, changes inproduction abroad as if produced with Swedish intensities, changes inthe ratio of world intensity to Swedish intensity, and changes in directuse (see Chapter 4.4.3).

– Analysis of the rationale behind using market exchange rates (MER)or purchasing power parity (PPP) exchange rates, suggesting the latterdue to that measure taking into account the exported products’ shareof the exporting country’s total output in a more relevant way (seeChapter 4.3.3).

� Results and features regarding data:

– The utilizing of recently (2010–2011) published environmental datafrom the Swedish environmental accounts, IEA and the internationalEDGAR database of global emissions.

– The construction of an Excel database with Swedish consumption-baseddata for the period 1993–2005, showing results for all analysed environ-mental variables on all aspects that was presented in Chapter 5 (forsome aspects presented there, only a selection of the environmentalvariables was shown). See Appendix F.

Chapter 6 Discussion and conclusions 67

� Empirical results:

– Consumption-based emissions of CO2 equivalents increase approximate-ly 20 % between 1993 and 2005, mainly driven by an increase in CH4

emissions. This should be compared to a decrease in the official pro-duction-based UNFCCC data. That means CO2 equivalents and allgreenhouse gases exhibits no EKC patterns and has not yet decoupledfrom growth in domestic final demand.

– In general, the increase in emissions is caused by increased demand forimported products which yields increasing emissions abroad.

– The levels of all emissions are considerably higher in the consumption-based case compared to the production-based case.

– Total fossil fuel use show no considerable difference to production-baseddata, whether in level or in trends (though consumption-based coaluse and gas use lie at higher levels). CO and NMVOC emissions aredecreasing as in the production-based data, but from higher levels.

– Impact from the consumption of services are in some instances ten timeshigher than the corresponding production-based impact.

– Impact from final demand categories (excluding direct use) are for bothenergy resource uses and emissions in general increasing. This holds es-pecially for the exports category, whose worldwide impact in the case ofCO2 equivalents has doubled in the whole period studied. The exportsdependence on fossil fuel use has also increased dramatically, approx-imately 80 % in the period studied (see details in the accompanyingExcel database introduced in Appendix F).

� Further research:

– Identification of a number of aspects and extensions to this study thatneed further research (see Chapter 6.5).


6.2 Uncertainties

The main uncertainties arise in the calculations of the resource uses and emissionsgenerated abroad. To begin with, this impact is based on the use of Swedishinput–output tables as a proxy for the industry structure of the rest of the world,where MRIO tables would be preferred. Building time series using SRIO tableswas still preferred as a first step in this research, and also since time series usingMRIO modelling has other limitations (see next section about comparisons toother studies). Also, in one study where different methods were compared, it wasconcluded that it is more important to obtain correct emission intensities thancorrect input–output coefficients for the Swedish import countries.3 However,future research should follow building time series using MRIO modelling.

Next in the uncertainties of impact abroad are the world average intensities. Onone hand they may be too high since, e.g. in the case of CO2, the Swedish im-port countries have a somewhat lower intensity than the world average intensity(though imports to importing countries are then excluded) – approximately 20 %lower.4 On the other hand, the PPP approach used implies a conservative esti-mate compared to the MER approach which is normally used in trade orientedenvironmental IOA studies (the MER approach yields approximately 20 % highervalues).5 Note though, since Swedish emissions occurring on the domestic territoryare added to the total figure, this uncertainty will become only about 10 %.

Other uncertainties include the allocation of bunkers between Swedish users andROW users (see Chapter 4.3.1), and the general problem of aggregation errorswhich occur in all IO models. Moreover, the required production to meet ourfinal demand may be somewhat overestimated due to including investments in theexports industry6 and due to feedback effects.7 Uncertainties arise also in the IOTupdating procedure for years missing official IOTs, but, accordingly, the years1995, 2000 and 2005 have in this sense no uncertainties.

When it comes to the linearity assumption in IO models – i.e. the assumptionthat economies of scale are not considered and increased final demand use thesame input structure – it is regarded as not being a relevant issue of concern inthis study. This study can be considered an accounting study only, i.e. we are notprojecting the emissions occurring if final demand would change, but we allocatelinearly the historical emissions that actually occurred over various final demandcategories and over final demand for various product groups. For instance, thisis evident in the case of exports whose direct and indirect effects are deductedlinearly. To deduct the exports from a hypothetical industry structure which onlywould serve the exports is irrelevant, since such an industry structure is not thestructure that we in fact had.

3Carlsson-Kanyama et al., 2007.4Based on Statistics Sweden, 2011g, and World Bank, 2010.5See Chapter 4.3.3 for details about the methods and assumptions in the calculations of the

world average intensities, and why the PPP approach was preferred.6See Chapter 3.3.6 for a discussion of investments in IO models.7See Chapter 3.3.1 and 4.2.3.


6.3 Comparison to other IOA and EKC studies

This study is the first study building a complete time series (1993–2005) of consec-utive IOAs regarding Swedish consumption-based emissions of CO2 equivalents.8

The most similar study to this regarding Swedish emissions of CO2 equivalents,is a study by Peters and Solli from 2010 which compares emissions in 2001 withemissions in 2004 using MRIO modelling.9 Their results lie in the same regionas in this present study (approximately between 100–120 Mt CO2eq/year). Thestrengths in their study is that it uses MRIO modelling with more detailed res-olution of emission intensities for the import countries. A weakness is that onlytwo years are analysed, which makes trend estimations uncertain. In that sense,this present study is more robust as it has built a longer time series. It is alsorobust in the sense that it uses fairly consistent IOTs and environmental data fromone single source (Statistics Sweden), whereas MRIO modelling is based on IOTswith varying degree of aggregation and coming from different years for the variouscountries included in the MRIO table.10

In the EKC studies by Kander and Lindmark,11 a SRIO model is used in con-structing an IOA-based 80-year-long time series of CO2 emissions, which exhibitsa typical EKC pattern. However, in their studies, Swedish emission intensities areapplied for the production occurring abroad, yielding too low values since Swedishimport countries have considerably higher emission intensities than Sweden it-self has.12 If superposing the values from the time series of consumption-basedemissions of CO2 from this present study upon their EKC-shaped data, the CO2

emissions will lie approximately at the peak of their EKC, and possibly be on therise as well. This doesn’t imply in itself that the consumption-based emissionsof CO2 are higher now than ever though. But it seems likely, since their EKC isprobably more correct in earlier years when the difference between the Swedishenergy system and the energy system abroad probably wasn’t so big with regardsto emission intensities (before the Swedish nuclear power plants were built).

The same conclusions regarding non-existent EKC patterns in IOA-based timeseries of SO2 emissions seem not be possible to draw with the results from thisstudy. Even though SO2 emissions in the second time series seem to be rising at alevel of approximately 250 000 tonnes per year, the peak in production-based dataoccurred in the end of the 1960s at a level of 960 000 tonnes per year.13 Thus,it is unreasonable to believe that consumption-based data in that time was lowerthan 250 000 tonnes per year.

8And some other variables. However, IOA-based time series of only CO2 have been analysedbefore in Lindmark, 2001, and Kander and Lindmark, 2006, and in Statistics Sweden, 2003,Statistics Sweden, 2011h, and Peters et al., 2011.

9Peters and Solli, 2010.10See e.g. GTAP, 2011.11Lindmark, 2001, and Kander and Lindmark, 2006.12Statistics Sweden, 2011g, and World Bank, 2010.13Johansson and Kristrom, 2007.


6.4 Conclusions

Reliability of results

Even though more detailed analyses are needed to get more robust results (seefurther research in Chapter 6.5), the results seem to correlate quite well withresults from similar studies – at least in the case of CO2 equivalents. The resultscould be a little bit high due to the world average intensities, but this is on theother hand compensated by conservative estimates due to the PPP approach. Anadvantage is also that the time series is built on consistent IOTs and environmentaldata from one single source (Statistics Sweden). All in all, this means the resultsfrom this study can be considered fairly reliable.

No decoupling and no EKC pattern in Swedish consumption-basedgreenhouse gas emissions

As regards the EKC hypothesis, many earlier studies have shown that even thoughlocal environmental indicators often exhibit EKC shapes, this is not the case forglobal indicators like CO2 emissions.14 Official Swedish data have suggested Swe-den is an exception in this matter, and many others have pointed out Sweden as acountry that has been able to decouple economic growth from increasing emissionsof CO2 and other greenhouse gases.15 However, this present study suggests thateven in the case of Sweden, greenhouse gases increase and a decoupling has notoccurred when considering the emissions caused worldwide by our consumption.

What has triggered the increase in greenhouse gases?

Has the growth in GDP or in domestic final demand even been the main causefor the increasing emissions of greenhouse gases? The study suggests that it isindeed the increase in our final demand that has triggered these emissions to in-crease. This is pointed out by the decomposition analysis, which suggests that ourincreased demand for imported products has driven the increase in emissions.16

This can be explained by, although we have a positive and increasing trade bal-ance, the imported products have higher emission intensities than the productswe produce for exports. Accordingly, the increase in our consumption has beenpossible at the expense of increased emissions abroad.17 This has important im-plications for climate change negotiations where emission reductions need to be

14See e.g. Galeotti, 2003, and Carson, 2010.15E.g. OECD, 2011, NIER, 2011.16Even though bunkers make the levels higher than in official UNFCCC data, they seem not

to have contributed to the increase in a significant way.17This is also the conclusion in Peters et al., 2011, but there with regard to increased con-

sumption in the developed world at the expense of higher emissions in the developing world –referred to as “weak carbon leakage”.


the obligation of those countries who through their consumption and way of livingare responsible for the emissions to occur.

On the other hand, if the world would have the same development of greenhousegases as the official Swedish production-based data, then we would have decreas-ing emissions at the same time as final demand was increasing. But the world isstill not there, which may imply that increasing Swedish final demand as a ne-cessity means increased emissions worldwide (if we were not to cut down heavilyon imports). It could well be that the development of world emissions of CO2

equivalents do have an EKC-shape, but that we are still too far left on this EKCthat it would be disastrous for us to wait until we have passed its peak.

Thus, Sweden has done a fairly good job in taking its responsibility to reduce itsterritorial production-based emissions of greenhouse gases. But – as this studysuggests – we are still responsible for increasingly contributing to higher concen-trations of greenhouse gases in the atmosphere through our consumption and wayof living.

Is growth the ultimate environmental problem?

What can this study tell us about growth in general as being either the ultimateenvironmental problem causing all the other environmental problems to occur, oras being a necessity in order to find solutions to decrease environmental impact?We have found that for some resource uses and emissions decoupling has indeedoccurred and for some others decoupling has not occurred. More environmentalvariables like material use and waste flows need be considered to get a more com-prehensive picture, and to be able to find out with more certainty whether growthis desirable or not.18 In the case of greenhouse gases, this study has showed thatthe arguments in favor of growth in consumption have not been convincing so far.

From problem formulations to solutions

To conclude, this study belongs to the problem formulation side of the environmen-tal problems–solutions dichotomy. Its aim has been to contribute to an accuratedescription of our environmental problems and their causes, in order to betterknow where to look for solutions to these problems. Accordingly, although moreresearch is needed to get more certain results here, what is even more important tofollow hereafter is research focusing on the solution side. An overview of both thesekinds of further research is presented in the following section. See also Chapter2.3.2 for an overview of proposed solutions.

18However, production-based data of waste flows in Sweden show a steady increase – see e.g.Sjostrom and Ostblom, 2010. See Krausmann et al., 2009 for a global outlook on material use.


6.5 Further research

Further research to improve and extend the model used in this study is needed.Also the objects of study could be extended in several ways, and even solutionsneed be pursued. Some of the most important points include:

� Methodological improvements and extensions:

– Construct time series based on trade data and intensities of Swedishtrading partners, as a comparison to the world average intensities ap-proach.

– More in-depth analysis of the various factors affecting the energy usesand emissions caused, such as the causes behind the increased CH4 andSO2 emissions. More detailed analysis of the contribution from bunkers.

– Include land use, land-use change and forestry (LULUCF) data.

– Perform a structural decomposition analysis based on IO-tables in con-stant prices.

– Improve the IOT updating method with RAS techniques.

– Construct time series based on MRIO modelling.

– Include the use of investments in the intermediate matrix in dynamicIO-modelling.

– Cross-sectional analysis of environmental impact over increasing incomegroups.

� Extensions of system boundaries and objects of study:

– Extensions of objects of study: Total energy use (including electricity),exergy and emergy use, virtual water, ecological footprint, pressureon biological stocks and ecosystem services (e.g. our contribution tooverfishing), material use and waste flows, water pollution, emissions ofpersistent organic pollutants.

– Temporal extensions: The extension of the time series backwards andforwards in time.

– Geographical extensions: The study of other countries as well, andultimately the whole world.

� Solutions:

– Explore and analyse solutions to the environmental problems identifiedin the research presented in this report and in the above suggested fur-ther research. See Chapter 2.3.2 for an overview of proposed solutions.

Recommended readings

Some of the references that have been of particular importance for this studyare presented below for those who want to read more. Full references of theserecommendations are given in the reference list in the following chapter.

A systems theory approach for analysing environmental problems at various systemlevels is presented in the must-read paper Leverage Points: Places to Intervenein a System by Donella H. Meadows, 1999. A good textbook introducing thefield of industrial ecology is Industrial Ecology and Sustainability Engineering byThomas E. Graedel and Braden R. Allenby, 2010. The field of ecological economicsis inspiredly introduced in Ecological Economics. Principles and Applications byHerman E. Daly and Joshua Farley, 2004.

A recent contribution to the growth debate is Prosperity without Growth. Eco-nomics for a Finite Planet by Tim Jackson, 2009, which also presents severalimportant concepts in the field, including decoupling and the IPAT equation. Therebound effect is discussed in Energy Efficiency and Sustainable Consumption.The Rebound Effect edited by Horace Herring and Steve Sorrell, 2009. An im-portant Swedish study analysing economic growth is the dissertation Economicgrowth, energy consumption and CO2 emissions in Sweden 1800–2000 by AstridKander, 2002. Another important Swedish dissertation in this field is Growthversus the Environment – Is There a Trade-off? by Per Kageson, 1997.

Input–output analysis is very well covered in Ronald E. Miller and Peter D.Blair’s classical textbook Input–Output Analysis. Foundations and Extensionsfrom 1985, now in an extended second edition from 2009. For environmental input–output analysis, a good introduction is Environmental Life Cycle Assessment ofGoods and Services. An Input–Output Approach by Chris T. Hendrickson et al.,2006. Various interesting environmental applications are also given in Handbookof Input–Output Economics in Industrial Ecology edited by Sangwon Suh, 2009.

Solutions within the frame of conventional economic theory are given in the opti-mistic Factor Five. Transforming the Global Economy through 80% Improvementsin Resource Productivity by Ernst von Weizsacker et al., 2009. Non-mainstreamsolutions are given in The Performance Economy by Walter R. Stahel, 2010, whoproposes an economy based on the sales of functions instead of the sales of prod-ucts. In Managing Without Growth. Slower by Design, Not Disaster by Peter A.Victor, 2008, a non-growth-based model of an economy is presented.

73

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http://dx.doi.org/10.1111/j.1749-6632.2009.05284.x

88 References

Waugh, F.V., 1950. Inversion of the Leontief matrix by power series. Economet-rica, 18 (2), 142–154.http://dx.doi.org/10.2307/1907265

Weber, C.L. and Matthews, H.S., 2007. Embodied environmental emissions in U.S.international trade, 1997–2004. Environmental Science and Technology, 41 (14),4875–4881.http://dx.doi.org/10.1021/es0629110

Weber, C.L. and Peters, G.P., 2009. Climate change policy and internationaltrade: policy considerations in the US. Energy Policy, 37 (2), 432–440.http://dx.doi.org/10.1016/j.enpol.2008.09.073

Weisz, H. and Duchin, F., 2006. Physical and monetary input–output analysis:what makes the difference? Ecological Economics, 57 (3), 534–541.http://dx.doi.org/10.1016/j.ecolecon.2005.05.011

Wiedmann, T., 2009. A review of recent multi-region input–output models usedfor consumption-based emission and resource accounting. Ecological Economics,69 (2), 211–222.http://dx.doi.org/10.1016/j.ecolecon.2009.08.026

Wiedmann, T., Minx, J., Barrett, J. and Wackernagel, M., 2006. Allocatingecological footprints to final consumption categories with input–output analysis.Ecological Economics, 56 (1), 28–48.http://dx.doi.org/10.1016/j.ecolecon.2005.05.012

Wiedmann, T., Wood, R., Minx, J.C., Lenzen, M., Guan, D. and Harris, R., 2010.A carbon footprint time series of the UK – results from a multi-region input–output model. Economic Systems Research, 22 (1), 19–42.http://dx.doi.org/10.1080/09535311003612591

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Ostblom, G., 1980. Energianvandningen i Sverige 1965–1978. Forskningsgrup-pen for energisystemstudier, Nationalekonomiska institutionen, Stockholms uni-versitet. Skrift Nr 1980:1.

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Appendices

91

92 Glossary and abbreviations Appendix A

Appendix A

Glossary and abbreviations

Aggregate E.g. when two different emissions are put together, considered as onehomogeneous group of emissions. Implies loss of information.

Basic prices Prices not including taxes less subsidies. It is the money the pro-ducer gets after the state has taken their part which was included in themarket prices.

Bunkers Fuels or the emissions from these fuels used in international transporta-tion (maritime or aviation).

Carbon leakage Emissions of greenhouse gases outside the domestic territorydue to regulations or increased consumption inside the domestic territory.

CH4 Methane, a greenhouse gas 21 times more powerful than CO2. Emitted frome.g. the livestock industry.

CO Carbon monoxide, a toxic gas resulting from combustion of carbon in oxygen-deficient environments, e.g. in vehicles.

CO2 Carbon dioxide, the most common greenhouse gas, emitted from the burningof fossil fuels in energy production and transportation, and in the cementindustry. Sweden emit approximately 60 million tonnes per year, globallyapproximately 30 billion tonnes per year.

CO2eq CO2 equivalents, the amount of greenhouse gas emissions taking into ac-count that other greenhouse gases besides CO2 has a higher global warmingpotential than CO2 itself. E.g. one tonne of methane becomes 21 tonnes ofCO2eq, and one tonne of N2O becomes 310 tonnes of CO2eq.

Consumption-based, consumption perspective Calculations of energy useor emissions occurring through the whole supply chain, as a consequence ofthe final consumption of a product. Compare production-based, productionperspective.

Constant prices Prices stripped from changes caused by inflation, only reflectingreal volume changes. Used when comparing economic values between years,e.g. the development of GDP.

Current prices Prices including inflation.

Direct use, environmental direct use The energy use or the emissions occur-ring in the usage phase of a product, e.g. petrol for the usage of a car orheating of housing.

Depreciation The wearing out of capital, value reduction of capital .

Appendix A Glossary and abbreviations 93

Domestic final demand That part of the final demand that represents whatthe domestic users purchase, i.e. the final demand less exports. CompareFinal demand of domestic products.

Downstream In this study, the usage phase and the disposal phase of a product.Or anything happening later on from a certain point in the supply chain.

Ecological footprint A measure of the area needed to take care of all the envi-ronmental impact a product or an individual causes.

EKC Environmental Kuznets curve.

Environmental input–output analysis The usage of input–output analysis com-bined with intensities of environmental flows per monetary value, to estimatethe environmental impact throughout the whole supply chain.

Environmental Kuznets curve A hypothesis saying that environmental degra-dation as a function of economic level, will take an inverted U-shaped form.

FD Final demand.

Feedback effect Imports to a country that have been exported from the samecountry in an earlier stage of the supply chain.

Final consumption The same as final demand.

Final demand Purchases done by private and public consumers, purchases donefor investments, and exports (purchases done by the rest of the world). Alsodenoted as final consumption, or final use. It is final in the sense that it isnot used for further production. Compare Intermediate use.

Final demand of domestic products Purchases done by the consumer, invest-ment and exports categories, of products produced domestically, thus notincluding imports. Compare Domestic final demand.

Final demand of imports Purchases done by the consumer, investment andthe exports category, of products produced abroad.

Final use The same as final demand.

GDP Gross domestic product.

Gross domestic product The sum of all industries’ value added in a country.Also the sum of consumption, investments and net exports (exports lessimports). It is gross in the meaning that also the depreciation part of theinvestments is included.

Gross output The output or production value from an industry, including allinputs of other products. It is gross in the meaning that both the value ofthe production that the industry has performed (the value added), and theproduction other industries has performed for the first industry’s input, arecounted. Not the same as gross in Gross domestic product.


Input Some kind of resource, often a product, needed in the production of prod-ucts. Mostly measured in monetary values (exception: physical IO-tables).

Input–output analysis An economic method used to analyse the productionneeded throughout the whole supply chain in order to satisfy a certain kindof final demand.

Input–output table A table showing the input of products needed per usercategories, i.e. intermediate users (products’ use of products) and final users.The input–output table is a converted use table. It differs from the usetable in that the intermediate users are products (imaginary homogeneousindustries producing only one product) instead of industries.

Intensities The amount of resources needed or emissions generated per dollar’sworth of products. Intensities link economic flows with physical flows, sothat physical flows can be estimated with the use of economical data incombination with intensities, i.e. by multiplying the latter two.

Intermediate matrix The product x product table in the input–output table orthe product x industry table in the use table (there normally called the usematrix). The intermediate matrix describes the intermediate use of productsin contrast to the final use of products.

Intermediate use Purchases done by industries and used as inputs in produc-tion. Also denoted as intermediate demand or intermediate consumption.Compare Final demand.

IO Input–output. E.g. IO-model, IO-table.

IOA Input–output analysis.

IOT Input–output table.

kt Kiloton, thousand tonnes.

LCA Life cycle assessment.

Leontief inverse A matrix describing the total amount of various products (alonga column) needed throughout the whole supply chain to satisfy the final con-sumption of some set of products (each column representing some kind offinal consumed product each). In this report denoted with L = (I −A)−1.

Make matrix The product x industry matrix in the supply table.

Market prices Basic prices plus taxes less subsidies.

Matrix of technical coefficients The matrix describing the value of inputsneeded in the production of products, per dollar’s worth of total inputs.In this report denoted with A.

Appendix A Glossary and abbreviations 95

MER Market exchange rates. The exchange rates normally used when differentcurrencies are exchanged for each other.

MRIO Multi-regional input–output. MRIO models include IOTs from variousregions or countries.

Mt Megaton, million tonnes.

N2O Nitrous oxide. A greenhouse gas 310 times more powerful than CO2. Emit-ted e.g. in agriculture and in industrial processes.

NDP Net domestic product.

Net domestic product The sum of consumption, net investments and net ex-ports (exports less imports). Net investments are investments less depre-ciation, i.e. the part of investments which increase the capital stock (seeFigure 2.6).

NMVOC Non-methane volatile organic compound, a group of organic compoundsemitted from e.g. car traffic and industrial processes.

NOx Nitrogen oxides, i.e. NO and NO2. Among the most important gases respon-sible for the acidification of ecosystems. Emitted in combustion processese.g. from car traffic.

Output In this study mostly the same as gross output, i.e. the value of a product,including all the inputs needed for its production, including wages going tolabor force inputs needed in the production (value added). Sometimes itmeans only the value added part of e.g. an industry’s output, but it shouldthen really be denoted as net output.

PPP Purchasing power parity. Exchange rates which take into account the factthat a certain amount of money expressed in a common currency has thepower to buy various amounts of the same goods depending on country.

Production-based, production perspective Energy use or emissions occur-ring inside a country’s territory, without the inclusion of indirect use oremissions occurring abroad due to imports.

Products In this study either goods or services. Can be divided into SNI groupswhich correspond to the various industries producing the products.

ROW Rest of the world.

SNA System of national accounts. The accounting system standard developedby UN and used by national accounts offices all around the world.

SNI Swedish Standard Industrial Classification (Svensk naringsgrensindelning).The standard in which Swedish industries are divided into various groups de-noted by SNI codes. The classification of products is based on this standard.


Every row and column in the intermediate matrix of the use table and theinput–output table and in the make matrix of the supply table correspondto a SNI code. SNI is based on the EU standard NACE. See Appendix G.

SO2 Sulfur dioxide, one of the most important gases responsible for the acidifica-tion of ecosystems. Emitted in the combustion of fossil fuels.

SRIO Single-regional input–output. SRIO models use a single input–output tablefrom a single country.

Supply The flow of products going into the society, later on used (i.e. purchased)by the industry or the final consumers. Includes both products produceddomestically, and imports, i.e. products produced abroad.

Supply chain The chain of suppliers (industries) transforming inputs (ultimatelyraw materials) step by step to a finished product for final use.

Supply table A table showing the various products produced by the variousindustries as well as imports of these products.

SUT Supply and use table.

TWh Terawatthours. The total Swedish energy supply has been around 600TWh per year the last 20 years.

UNFCCC United Nations Framework Convention on Climate Change. A treatysigned at the Rio summit in 1992. The Kyoto protocol is an amendment tothis treaty. As a part of the treaty, Sweden submit emission reports to theUNFCCC secretariat annually.

Upstream The production occurring in an earlier stage in the supply chain.

Use The various ways in which the supply flow coming into the society is used anddistributed over various user categories (i.e. various consumer categories).These categories could be intermediate users (consumption carried out byindustries) or various final users (private and public consumers, investorsand consumers abroad (exports)).

Use matrix The intermediate product x industry matrix in the use table.

Use table A table showing the input of products needed per user category, i.e. pervarious intermediate users (industries) and per various final users (privateand public consumers, investors and exports).

Value added Revenues of production less costs for product inputs.

World average intensities In this study, the resource use or emission intensitiesof the various products groups produced in the average world industries.Correspond to EPPP

i and EMERi in equation (4.21).

Appendix B List of variables 97

Appendix B

List of variables

Ad The domestic part of the matrix of technical coefficients: Ad = Fd x−1p

or (adij) = (fdij/x

pj). The element adij represents the use of domestic

input of product i per dollar’s worth of production of product j.

Am The imports part of the matrix of technical coefficients: Am = Fm x−1p

or (amij ) = (fmij /x

pj). The element amij represents the use of imported

input of product i per dollar’s worth of production of product j.

Atot The matrix of technical coefficients, domestic plus imports: Atot =Ad + Am or (atotij ) = ((fd

ij + fmij )/xp

j). The element atotij represents theuse of domestic plus imported inputs of product i per dollar’s worthof production of product j.

Eind Environmental matrix of resource uses and emissions per industry. Theelement eindij represents resource use or emission of type i generateddirectly by industry j.

Ep Environmental matrix of resource uses and emissions per product:Ep = EindS

′c. The element epij represents resource use or emission

of type i generated directly by product j.

edir The environmental direct use vector. The element ediri represents directresource use or emission of type i generated directly by final consumersdownstream the event of consumption. This vector is originally dividedinto several columns, but here it is treated as a single vector.

Eswei The Swedish environmental intensity matrix: Eswe

i = Epx−1p . The

element ei,sweij represents resource use or emission of type i generated

directly in Sweden per dollar’s worth of product j.

EMERi World average intensity matrix based on the MER approach: EMER

i =kMERE

swei . The element ei,MER

ij represents resource use or emission oftype i generated directly abroad per dollar’s worth of product j.

EPPPi World average intensity matrix based on the PPP approach: EPPP

i =kPPPE

swei . The element ei,PPP

ij represents resource use or emission oftype i generated directly abroad per dollar’s worth of product j.

eswe The vector of Swedish total resource uses and emissions from bothindustry and direct use, including bunkers: eswe = Epi + edir. Theelement eswe

i represents resource use or emission of type i generateddirectly by industry and final consumers.

eworld The vector of global total resource uses and emissions. The elementeworldi represents resource use or emission of type i generated totally in

the whole world.

98 List of variables Appendix B

ec The vector of consumption-based resource uses and emissions gener-ated directly and indirectly throughout the whole supply chain due tofinal demand. The element eci represents resource use or emission oftype i generated.

etot The vector of consumption-based resource uses and emissions gener-ated directly and indirectly throughout the whole supply chain dueto total final demand (excluding exports) of domestic and importedproducts, including downstream effects in direct use (edir). The ele-ment etoti represents resource use or emission of type i generated. Seeequation (4.23).

Fd The intermediate product x product matrix of the domestic part ofthe input–output table. The element fd

ij represents the input of thedomestical products i in the production of all products j producedover a year.

Fm The intermediate product x product matrix of the imports part ofthe input–output table. The element fm

ij represents the input of theimported products i in the production of all products j produced overa year.

Ftot The intermediate product x product matrix of the domestic plus im-ports input–output table. The element f tot

ij represents the input of thedomestical and imported products i in the production of all productsj produced over a year.

G Aggregation matrix.

i The unit vector (a column vector with only ones).

k Ratio of world intensity to Swedish intensity vector. Could be kMER

or kPPP depending on whether the MER or the PPP approach isused. The element ki refers to the world–Sweden intensity ratio forthe resource use or emission type i. See equation (4.20).

I The identity matrix.

Ld The Leontief inverse, domestic: Ld = (I − Ad)−1. The element ldij

represents the total domestic production, direct and indirect, of prod-uct i needed throughout the whole supply chain per dollar’s worth ofconsumption of product j.

Ltot The Leontief inverse, total: Ltot = (I−Atot)−1. The element ltotij repre-

sents the total domestic and imported production, direct and indirect,of product i needed throughout the whole supply chain per dollar’sworth of consumption of product j.

m The vector of total imports per product.

Appendix B List of variables 99

S The make matrix of the supply table.

Sc The coefficient matrix of the make matrix: Sc = Sx−1ind .

U The intermediate use matrix of the use table.

xind The vector of total output per industry, equals to total domestic pro-duction per industry.

xind Diagonalization of the vector xind.

xp The vector of total output per product, equals to total domestic pro-duction per product, equals to total input per product.

xp Diagonalization of the vector xp.

yd The vector of final demand (including exports) of domestic products.The final demand vectors are each originally divided into several col-umns, but are here treated as single vectors.

ym The vector of final demand (including exports) of products producedabroad.

ytot The vector of final demand (including exports) of domestic productsand products produced abroad.

ynexpd The vector of domestic final demand (excluding exports) of domestic

products.

ynexpm The vector of domestic final demand (excluding exports) of products

produced abroad.

ynexptot The vector of domestic final demand (excluding exports) of domestic

products and products produced abroad.

100 Matrix algebraic conventions Appendix C

Appendix C

Matrix algebraic conventions

General conventions

� Matrices are in uppercase bold letters: A

� Vectors are in lowercase bold letters: x

� Elements in vectors or matrices are in lowercase, normal letters: x1

� For an element aij in the matrix A, i refers to the row number of thatelement, and j refers to the column number.

� A matrix or a vector could be denoted as A or (aij); these ways of writingare equivalent, i.e. A = (aij).

� The matrix I is the unity matrix, with only ones on the diagonal.

� The vector i is a unit vector with only ones in a column, e.g. i′ = ( 1 1 1 ).

� Denoting matrices or vectors with some attribute, is done in index position,e.g. Ad. For elements this is however denoted in exponent position, as indexposition is reserved for purpose of position of the element in the matrix,e.g. adij. This will probably not be any problem, since elements are seldompowered. Some times exponent position is used as well for matrices, e.g.in decomposition analysis where E0

i refers to intensities in year 0. Whenpowering is done, this will be evident from the context.

� Vectors are by default column vectors. Row vectors are consequently denotedby e.g. x′.

Diagonalizing

Diagonalizing of vector x is denoted x, which means that if x′ =(x1 x2 x3

),

then

x =

x1 0 00 x2 00 0 x3

.

In x−1 all elements on the diagonal are inverted, that is

x−1 =

1/x1 0 00 1/x2 00 0 1/x3

.

So doing F x−1, means to divide every element in the first column of F with x1,the second column with x2, and so on.

Appendix C Matrix algebraic conventions 101

Multiplication

Multiplication like Ay can be interpreted as

Ay = b⇒ a11 a12 a13a21 a22 a23a31 a32 a33

y1y2y3

=

y1 a11

a21a31

+ y2

a12a22a32

+ y3

a13a23a33

=

=

y1a11 + y2a12 + y3a13y1a21 + y2a22 + y3a23y1a31 + y2a32 + y3a33

=

b1b2b3

,

which means that the first column in A is multiplied by y1, the second columnin A is multiplied by y2, and the third column in A is multiplied by y3, whichafter adding the resulting columns leads to a new column vector b. If A is insteadmultiplied by a matrix Y , the same procedure is done fore each column in Yyielding subsequently as many columns in the resulting matrix B.

Aggregation

Aggregation of vector x, meaning that certain rows of x are put together, isaccomplished by e.g.

x = Gx⇒ 257

=

1 0 0 00 1 1 00 0 0 1

2417

,

showing that row number 2 and 3 are put together. Aggregation of matrix S sothat certain rows and corresponding columns are put together, is done by e.g.

S = GSG′ ⇒ 2 7 55 16 117 17 0

=

1 0 0 00 1 1 00 0 0 1

2 3 4 54 5 6 71 2 3 47 8 9 0

1 0 00 1 00 1 00 0 1

,

showing that rows 2 and 3 and columns 2 and 3 are put together.

102 Matrix algebraic conventions Appendix C

Element-wise multiplication

Since a matrix A = (aij), and A + B = (aij + bij), element-wise multiplicationbetween A and B can be expressed as (aij · bij). This is sometimes denoted asA⊗B, called the Habermard product. Accordingly,

A⊗B = (aij · bij) =

(a11 a12a21 a22

)⊗(

b11 b12b21 b22

)=

(a11b11 a12b12a21b21 a22b22

).

A similar Habermard division can then be defined as A � B which is the sameas (aij/bij). Sometimes a column vector is multiplied element-wise with all thecolumns of a matrix. If we have A and x, this is described as (aij · xi).

1

Environmental matrices built upon the Leontief inverse

Using element-wise multiplication it is possible to construct a sort of “environmen-tal Leontief inverse” matrix for a certain environmental impact. If the impact’sintensity vector is ei (e.g. describing the CO2 intensities of various products), thismatrix becomes

El = (eii · lij) ,

where the element elij denotes the emissions from the production of product ineeded directly and indirectly per dollar’s worth of consumption of product j.

A similar matrix is possible to construct using ordinary matrix multiplication in

EL = EiL ,

where Ei is the environmental intensity matrix (with eiij denoting resource use oremission of type i generated directly per dollar’s worth of production of productj), and the element eLij in EL denotes the total environmental impact of type icaused directly and indirectly per dollar’s worth of consumption of product j.2

Upon this result, a consumption-based environmental impact matrix describingenvironmental impact per environmental variable and per consumed product dueto any final demand y (not just per dollar) can be constructed through

Ec = (eLij · yj) .

Thus, the element ecij denotes the total environmental impact of type i caused bythe consumption of product j. An example of this matrix is shown in Appendix G.

1The dot in between the factors of e.g. (aij · bij) is not needed, only there for clarity.2Miller and Blair, 2009, discuss this matrix.

Appendix D Proof that An+1 converges to zero 103

Appendix D

Proof that An+1 converges to zero1

This adds to the derivation of the power series approximation of the Leontiefinverse, presented in equations (3.8) and (3.9), which assumed that An+1 → 0 ifn→∞.

We can assume that the column sums of A are all less than 1 since all productshave not only other products as inputs, but also labor force inputs, so the shareof product inputs must be less than 1. Saying this, we have at the same timesaid that all the elements aij of A are also each of them less than 1, and we alsoassume that they are equal to or greater than 0. Further on, we define the norm||A|| as the maximum element of A, i.e. ||A|| = max(aij), and we also define s asthe maximum column sum of A, i.e. s = max(

∑k akj).

Now, we will start off by examining if the maximum element of A2 is less thanthe maximum element of A:

||A2|| = ||AA|| = max(∑k

aikakj) ≤ max(||A||∑k

akj) = ||A||s < ||A|| ,

since s < 1. The sum∑

k aikakj in the equation above is the definition of matrixmultiplication. In the step just after that, we have exchanged ||A|| for aik sinceaik ≤ ||A||, so if the proof holds when inserting ||A||, it will be even more true foraik. Thus, apparently is ||A2|| ≤ ||A||s < ||A||, i.e. the maximum element of A2

is less than the maximum element of A.

The similar reasoning can now be done for the higher powers as well, yielding that

||An+1|| = ||AnA|| ≤ ||An||s ≤ ||An−1||s2 ≤ . . . ≤ ||A||sn → 0, n→∞,

since, again, s < 1. So the maximum element of An+1 goes to 0, which impliesthat the whole matrix An+1 → 0 as n→∞.

1Based on Physics Forums, 2010. A slightly different approach is found in Waugh, 1950, andin Miller and Blair, 2009.

104 SUT and IOT for Sweden 2005 Appendix E

Appendix E

SUT and IOT for Sweden 2005

Supply table, Sweden 2005 (basic prices, current prices)

Industries

ProductsAgricult. industry

Forest industry

…House- hold serv.

Total production per product Imports

Total supply at basic prices

Taxes less subs.

Total supply at market prices

Agricultural products (SNI 01) 36 2 38 14 52 19 71Forestry products (SNI 02) 20 2 22 4 26 26

… (SNI 03-94)

3 1Household services (SNI 95) 1 1 1

Total production per industry 39 21 1 5100 1100 6200 400 6600

(Unit: Billion SEK/year)

Use table, Sweden 2005 (market prices, current prices)

Industries Final demand

ProductsAgricult. industry

Forest industry

…House-hold serv.

Total intermed. use per product

Con-sumption

Gross investments Exports

Total final demand per product

Total supply per product

Agricultural products (SNI 01) 6 31 37 31 3 34 71Forestry products (SNI 02) 1 24 25 1 -1 1 1 26

… (SNI 03-94)21 6

Household services (SNI 95) 1 1 1

Total use per industry or FD 27 7 0 2700 2100 500 1300 3900 6600

Value added per industry 12 14 1 2400Total input per industry 39 21 1 5100

(Unit: Billion SEK/year)

Input-output table, Sweden 2005 (basic prices, current prices)

Products Final demand

ProductsAgricult. products

Forest products

…House-hold serv.

Total intermed. use per product

Con-sumption

Gross investments Exports

Total final demand per product

Total supply per product (output+imports)

Agricultural products (SNI 01) 4+1 27+3 31+4 5+9 2+1 7+10 38+14Forestry products (SNI 02) 1.2+0.1 20+4 21+4 1+0 -1.5+0 1+0 0.5+0 22+4

… (SNI 03-94)15+4 4+2

Household services (SNI 95) 1+0 1+0 1+0

Total use per product or FD 19+5 5+2 1900+700 1700+200 300+100 200+100 3200+400 5100+1100Taxes less subsidies 2 1 100 200 100 0 300 400Total use incl. taxes 26 8 0 2700 2100 500 1300 3900 6600

Value added per product 12 14 1 2400Total input per product 38 22 1 5100Imports 14 4 0 1100Total supply per product 52 26 1 6200

(Unit: Billion SEK/year) Note: Cells include domestic+imports figures.

Source : Statistics Sweden, 2008 and 2009.

Appendix F Organization of the Excel database 105

Appendix F

Organization of the Excel database

The Excel database is available at:http://www.fysast.uu.se/ges/en/marten-berglund

The database is divided into ten different files, organized in three levels – see FigureF.1 below. Arrows in the figure describe the relationships between the files, i.e.from which files the various files fetch data used in the sheet calculations.1,2

Original data, files on the base level:

S.xls The official supply-tables, from 1993 to 2005, in both revisions.

U.xls The official use-tables, from 1993 to 2005, in both revisions.

IO.xls The official IOTs, from 1995 and 2000 in the first revision, and 2000and 2005 in the second revision.

GDP.xls GDP time series and other economic data, for Sweden and for thewhole world.

E swe.xls Official Swedish environmental data from the Energy authority (en-ergy use, including bunkers) and from the Swedish reporting to UN-FCCC (emissions, excluding bunkers).

E mir.xls Environmental matrices (flows per industry) from the environmentalaccounts (including bunkers), from 1993–2005.

E world.xls Official global environmental data from IEA and from the EDGARdatabase. Including bunkers.

IO_r.xls

Main.xls

E_int.xls

S.xls U.xls IO.xls E_swe.xls E_mir.xls E_world.xlsGDP.xls

Figure F.1. Relations between the files in the Excel database.

1Only the most important relations are shown in the figure. Main.xls also fetches datadirectly from all the files on the base level except from IO.xls and E world.xls.

2Though not included in the calculations, two additional files are part of the database:Figs.xls (data from figures in report) and Results.xls (results sheets from Main.xls, see below).

http://www.fysast.uu.se/ges/en/marten-berglund

106 Organization of the Excel database Appendix F

Auxiliary calculation files, files on the middle level:

IO r.xls In this file, the domestic and imports shares in the IOTs are extracted.

E int.xls In this file, the environmental matrix from E mir.xls is converted froman energy uses or emissions x industry matrix, to an energy uses oremissions x product matrix. The corresponding intensity matrix iscalculated. The intensity ratio between the world and Sweden, is cal-culated.

Main calculation files, files on the top level:

Main.xls All the main calculations are done here. Data are fetched from the fileson the lower levels. The A matrix is generated and its correspondingLeontief inverse. The vectors and matrices describing required pro-duction per consumed products, as well as required energy use andgenerated emissions per consumed products, are calculated. All re-sults are gathered in the 8th sheet section of this file, in five separatesheets (see the table of contents of the file in the first sheet).

The database can be considered a vector valued function f(t), which as input, t,takes years, and as output pours out various consumption-based environmentaldata. The input, t, is given in cell [Main.xls]Tot!B3 and the output is generatedin the sheets in the 8th sheet section of the file Main.xls. The input t is actuallynot just a year, but also indicates which revision is to be used, denoted by a or b.Valid values for t are 1993a–2003a, and 2000b–2005b. A time series is generatedby entering such a year and revision in the cell mentioned, and then saving all theoutputs coming from that year and revision in a separate column. The same isrepeated for all years in that revision.

The output is divided onto five sheets, with the following contents:

Tot Consumption-based totals for various assumptions (PPP etc.), physicaltrade balances, economical data, official production based data, for allenvironmental variables.

IPAT IPAT data and indices for all environmental variables.

IDA Decomposition analysis data for all environmental variables.

Prod Product groups analysis, the environmental impact per various productgroups, for all environmental variables.

FD cat Environmental impact per the various final demand categories, for allenvironmental variables.

Calculations are done in accordance with what has been described in Chapter 4.The detailed description of these calculations are found in the table of contents-sheets, and directly as cell formulas in the various sheets.

Appendix G Excel tables 107

Appendix G

Excel tables

A selection of interesting tables from the Excel database is shown on the followingpages.

Page Description

108 SNI codes for the various product groups.

109 The Swedish matrix of technical coefficients Atot for 2005.

110 The Swedish Leontief inverse Ltot for 2005.

111 A consumption-based Swedish environmental impact matrix describ-ing worldwide environmental impact per environmental variable andper consumed product due to Swedish final demand in 2005 of domes-tic and imported products. Corresponds to the Ec matrix describedin Appendix C about environmental matrices (though Ec here is con-structed from several different environmental intensity matrices dueto distinct intensities in Sweden and abroad). Data are based on thePPP approach. Direct use is not part of these values, since this matrixonly describes the impact caused upstream per consumed product, notthe direct use impact by the final user (which can not be allocated perproduct).

112–116 The Tot sheet from Main.xls (slightly adjusted), showing the mainconsumption-based results for all environmental variables.

108 Excel tables Appendix G

SNI codes

01 Agriculture02 Forestry05 Fishing10-12 Extraction of energy resources13-14 Mining of metal ores, other mining and quarrying15-16 Food products, beverages and tobacco17 Textiles industry18 Textile products19 Tanning and dressing of leather20 Manufacture of wood and wood products21 Pulp, paper and paper products22 Publishing and printing23 Coke, refined petroleum products and nuclear fuel24 Chemicals and chemical products25 Rubber and plastic products26 Non-metallic mineral products27 Basic metals28 Fabricated metal products29 Machinery and equipment30 Office machinery and computers31 Electrical machinery and apparatus32 Radio, television and communication equipment33 Medical and optical instruments, watches and clocks34 Motor vehicles, trailers and semi-trailers35 Manufacturing of other transport equipment36 Furniture and other manufacturing37 Recycling/Samhall40 Electricity, gas, steam and hot water41 Water45 Construction50-52 Auto sales, wholesale trade, retail trade55 Hotels and restaurants60 Land transport, pipelines61 Water transport62 Air transport63 Supporting transport activities64 Post and telecommunications65 Banking66 Insurance and pension funding67 Other financial activities70 Real estate activities71 Renting of machinery and equipment72 Computer and related activities73 Research and development74-75 Other business activities and public administration80 Education85 Health and social work90 Sewage and refuse disposal91 Membership organizations92 Recreational, cultural and sporting activities93 Other service activities95 Private households with employed persons


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The

Swed

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Leon

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nver

se L

tot

for 2

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SN

I cod

e01

0205

10-1

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2021

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2425

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2829

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3435

3637

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0.02

0.03

0.04

0.00

0.02

0.02

0.02

0.02

0.02

0.01

0.01

0.01

0.02

0.02

0.02

0.02

0.02

0.02

0.05

0.02

0.01

0.02

0.01

0.02

0.05

0.05

0.02

0.03

0.01

0.02

0.03

0.05

0.01

0.00

230.

070.

040.

150.

050.

030.

040.

030.

020.

020.

030.

040.

021.

080.

050.

030.

060.

050.

020.

020.

020.

010.

000.

010.

020.

020.

020.

220.

040.

020.

030.

020.

020.

060.

140.

140.

040.

010.

000.

000.

010.

010.

020.

010.

010.

010.

010.

010.

040.

010.

010.

010.

0024

0.09

0.01

0.04

0.05

0.03

0.06

0.19

0.05

0.10

0.03

0.09

0.05

0.05

1.25

0.32

0.06

0.04

0.03

0.04

0.04

0.03

0.00

0.04

0.04

0.04

0.07

0.03

0.02

0.06

0.03

0.02

0.02

0.02

0.02

0.02

0.01

0.01

0.01

0.00

0.01

0.01

0.02

0.02

0.03

0.01

0.01

0.02

0.02

0.01

0.02

0.03

0.00

250.

020.

010.

010.

050.

010.

040.

020.

030.

010.

020.

020.

020.

040.

031.

080.

030.

020.

020.

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030.

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020.

010.

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010.

010.

010.

010.

010.

000.

000.

000.

010.

010.

010.

010.

010.

000.

010.

020.

010.

010.

010.

0026

0.01

0.00

0.01

0.01

0.02

0.01

0.02

0.01

0.00

0.02

0.01

0.00

0.01

0.01

0.01

1.10

0.02

0.01

0.01

0.01

0.01

0.00

0.01

0.02

0.01

0.01

0.01

0.01

0.01

0.07

0.00

0.01

0.00

0.00

0.01

0.00

0.00

0.00

0.00

0.00

0.01

0.01

0.00

0.00

0.01

0.00

0.00

0.00

0.00

0.00

0.01

0.00

270.

030.

020.

030.

030.

040.

020.

050.

020.

020.

030.

020.

020.

030.

020.

070.

061.

480.

260.

150.

140.

100.

000.

090.

130.

100.

160.

070.

020.

040.

060.

020.

010.

010.

020.

030.

010.

020.

010.

000.

010.

020.

030.

020.

020.

020.

010.

010.

020.

010.

010.

020.

0028

0.02

0.02

0.04

0.04

0.05

0.03

0.02

0.02

0.02

0.07

0.02

0.02

0.04

0.02

0.04

0.05

0.06

1.17

0.15

0.07

0.04

0.00

0.06

0.10

0.10

0.08

0.05

0.01

0.08

0.08

0.02

0.02

0.02

0.03

0.03

0.02

0.02

0.01

0.01

0.01

0.02

0.02

0.03

0.02

0.02

0.01

0.01

0.02

0.01

0.01

0.02

0.00

290.

060.

070.

020.

050.

130.

030.

030.

020.

030.

040.

050.

020.

050.

020.

040.

030.

050.

041.

200.

030.

020.

000.

050.

080.

050.

050.

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030.

030.

050.

020.

020.

020.

020.

020.

010.

010.

000.

000.

010.

010.

050.

020.

020.

020.

010.

010.

020.

010.

010.

020.

0030

0.00

0.00

0.01

0.01

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

1.11

0.02

0.00

0.01

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

310.

010.

010.

020.

010.

020.

010.

010.

010.

010.

010.

010.

020.

020.

020.

030.

020.

020.

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090.

121.

340.

000.

160.

050.

060.

020.

010.

020.

020.

040.

020.

010.

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020.

010.

050.

010.

010.

010.

010.

020.

020.

030.

020.

010.

010.

010.

010.

010.

020.

0032

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

1.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

330.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

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000.

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000.

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120.

000.

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000.

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000.

000.

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000.

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010.

000.

000.

000.

000.

000.

010.

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010.

000.

030.

000.

000.

000.

010.

0034

0.02

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.02

0.01

0.02

0.02

0.06

0.01

0.01

0.00

0.01

1.56

0.02

0.02

0.01

0.01

0.01

0.01

0.06

0.01

0.01

0.01

0.01

0.01

0.01

0.00

0.00

0.01

0.01

0.03

0.01

0.02

0.01

0.00

0.00

0.01

0.01

0.01

0.01

0.00

350.

000.

010.

110.

010.

010.

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010.

000.

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000.

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270.

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000.

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110.

140.

030.

000.

000.

000.

000.

010.

020.

000.

010.

050.

000.

000.

010.

000.

000.

000.

0036

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.03

0.02

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.01

0.00

0.01

0.00

0.00

0.03

0.01

1.15

0.00

0.00

0.00

0.01

0.00

0.01

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.00

0.00

0.00

0.01

0.01

0.00

0.00

370.

000.

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000.

000.

0040

0.05

0.02

0.02

0.04

0.04

0.04

0.03

0.02

0.03

0.04

0.08

0.02

0.05

0.03

0.04

0.03

0.05

0.03

0.02

0.02

0.02

0.00

0.02

0.02

0.02

0.03

0.03

1.07

0.05

0.02

0.02

0.02

0.02

0.02

0.02

0.02

0.01

0.00

0.01

0.01

0.02

0.02

0.01

0.01

0.02

0.01

0.01

0.03

0.02

0.03

0.01

0.00

410.

000.

000.

000.

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000.

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000.

000.

000.

000.

020.

000.

000.

000.

000.

000.

000.

000.

000.

010.

010.

0045

0.04

0.03

0.01

0.02

0.02

0.02

0.01

0.02

0.02

0.02

0.02

0.02

0.02

0.01

0.02

0.02

0.02

0.02

0.02

0.02

0.02

0.00

0.02

0.02

0.02

0.02

0.02

0.04

0.06

1.02

0.02

0.03

0.01

0.02

0.02

0.02

0.04

0.02

0.04

0.02

0.12

0.02

0.02

0.02

0.05

0.02

0.01

0.02

0.03

0.03

0.02

0.00

50-5

20.

120.

050.

120.

070.

080.

100.

070.

060.

070.

070.

090.

050.

070.

050.

080.

090.

160.

090.

110.

100.

080.

000.

080.

120.

090.

090.

060.

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040.

081.

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090.

100.

050.

090.

060.

040.

010.

010.

020.

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040.

040.

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020.

030.

110.

040.

060.

050.

0055

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.02

0.00

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

1.01

0.01

0.01

0.02

0.02

0.03

0.01

0.01

0.01

0.01

0.01

0.02

0.02

0.01

0.01

0.01

0.03

0.02

0.02

0.01

0.00

600.

050.

020.

080.

130.

080.

080.

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110.

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120.

140.

060.

120.

040.

050.

120.

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050.

050.

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200.

120.

130.

400.

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070.

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020.

0061

0.01

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0.02

0.01

0.02

0.02

0.01

0.02

0.01

0.01

0.03

0.02

0.01

0.01

0.01

0.01

0.00

0.01

0.01

0.01

0.02

0.01

0.00

0.00

0.01

0.01

0.01

0.01

1.21

0.02

0.06

0.00

0.00

0.00

0.00

0.00

0.01

0.00

0.01

0.00

0.00

0.00

0.01

0.00

0.00

0.00

0.00

620.

010.

010.

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010.

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070.

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0063

0.06

0.02

0.09

0.17

0.08

0.11

0.10

0.12

0.05

0.14

0.17

0.07

0.16

0.05

0.06

0.15

0.09

0.06

0.06

0.05

0.04

0.00

0.04

0.07

0.05

0.10

0.14

0.03

0.03

0.04

0.08

0.05

0.07

0.29

0.33

1.13

0.03

0.01

0.01

0.01

0.02

0.05

0.03

0.03

0.02

0.02

0.01

0.05

0.02

0.03

0.02

0.00

640.

020.

020.

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100.

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230.

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050.

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070.

020.

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0.03

0.02

0.03

0.02

0.02

0.02

0.02

0.02

0.02

0.02

0.02

0.02

0.03

0.02

0.02

0.02

0.02

0.02

0.02

0.02

0.02

0.00

0.02

0.03

0.02

0.03

0.02

0.02

0.02

0.02

0.02

0.02

0.02

0.03

0.02

0.02

0.02

1.06

0.08

0.03

0.06

0.02

0.02

0.02

0.02

0.01

0.01

0.03

0.02

0.02

0.02

0.00

660.

010.

000.

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0067

0.01

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0.00

0.01

0.00

0.01

0.00

0.01

0.00

0.01

0.01

0.00

0.01

0.00

0.01

0.00

0.01

0.01

0.01

0.01

0.01

0.00

0.01

0.01

0.01

0.01

0.00

0.00

0.01

0.00

0.00

0.00

0.00

0.01

0.00

0.00

0.01

0.01

0.00

1.02

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

700.

030.

020.

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070.

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160.

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161.

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100.

120.

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050.

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110.

090.

0071

0.01

0.01

0.02

0.02

0.01

0.01

0.02

0.03

0.02

0.02

0.02

0.02

0.02

0.01

0.01

0.01

0.02

0.02

0.01

0.01

0.01

0.00

0.01

0.01

0.01

0.02

0.02

0.01

0.04

0.02

0.01

0.01

0.03

0.03

0.14

0.04

0.03

0.01

0.00

0.02

0.01

1.02

0.01

0.02

0.01

0.01

0.01

0.03

0.02

0.02

0.01

0.00

720.

020.

020.

020.

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020.

0073

0.12

0.09

0.09

0.16

0.13

0.18

0.18

0.17

0.14

0.12

0.14

0.21

0.16

0.27

0.20

0.16

0.14

0.15

0.22

0.24

0.39

0.00

0.19

0.29

0.17

0.19

0.14

0.11

0.10

0.14

0.16

0.12

0.12

0.19

0.18

0.13

0.22

0.13

0.07

0.18

0.10

0.17

0.21

1.24

0.13

0.06

0.07

0.24

0.13

0.17

0.10

0.00

74-7

50.

010.

010.

010.

010.

010.

010.

010.

020.

010.

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010.

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0080

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.00

0.00

0.00

0.01

0.00

0.00

0.00

0.00

0.01

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.00

0.01

0.01

0.01

0.01

1.01

0.01

0.00

0.01

0.00

0.00

0.00

850.

010.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

020.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

010.

001.

010.

000.

000.

010.

000.

0090

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.00

0.00

0.01

0.00

0.00

0.00

0.00

0.00

0.01

0.00

0.00

0.00

0.01

0.00

0.00

0.01

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.01

0.01

0.00

0.00

0.00

0.00

0.00

0.00

0.01

0.04

0.01

0.01

0.01

0.01

0.01

0.00

1.04

0.00

0.01

0.00

0.00

910.

000.

000.

000.

000.

000.

000.

010.

020.

010.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

010.

000.

000.

010.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

011.

000.

000.

000.

0092

0.01

0.00

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.07

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.00

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.05

0.01

0.01

0.01

0.01

0.01

0.01

0.03

0.01

0.01

0.00

0.01

0.01

1.11

0.01

0.00

930.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

010.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

000.

001.

000.

0095

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

1.00


Con

sum

ptio

n-ba

sed

envi

ronm

enta

l im

pact

per

env

ironm

enta

l var

iabl

e an

d pe

r con

sum

ed p

rodu

ct d

ue to

Sw

edis

h fin

al d

eman

d in

200

5, P

PP a

ppro

ach

Env

ironm

enta

l var

iabl

e \ S

NI c

ode

0102

0510

-12

13-1

415

-16

1718

1920

2122

2324

2526

2728

Oil

3.34

-0.1

30.

37-0

.10

-0.0

310

.70

0.45

0.99

0.29

0.54

0.34

0.63

2.37

1.22

0.17

0.37

-0.1

41.

04C

oal

0.27

0.00

0.01

-0.0

1-0

.01

1.35

0.14

0.13

0.07

0.06

0.08

0.13

0.33

2.43

0.11

0.44

-0.0

30.

23G

as0.

84-0

.01

0.04

-0.0

3-0

.01

4.05

0.25

0.27

0.11

0.10

0.08

0.17

5.27

1.67

0.14

0.11

-0.1

20.

60To

tal f

ossi

l fue

ls4.

45-0

.15

0.41

-0.1

5-0

.05

16.1

00.

841.

390.

470.

700.

510.

937.

975.

320.

430.

92-0

.30

1.87

CO

21

779

214

-41

099

163

658

-68

621

-15

392

5 97

9 07

235

9 43

863

9 10

620

2 93

728

6 66

220

7 76

436

8 44

92

517

616

1 63

8 30

517

0 04

959

9 67

2-2

03 2

481

030

137

CH

430

7 09

5-1

8933

1-2

959

-60

378

225

2 54

313

410

13 5

531

274

953

2 38

857

494

11 0

071

151

819

-529

4 35

2N

2O12

209

-13

17-1

02-4

17 4

0998

437

462

6956

110

1 99

295

757

54-2

115

6C

O2e

q12

013

018

-49

001

176

000

-162

355

-17

800

19 3

18 6

2244

3 22

71

056

053

630

780

334

797

245

232

452

752

4 34

2 44

52

166

207

211

884

633

507

-220

838

1 16

9 78

1S

O2

2 18

8-4

570

4-2

90-6

220

323

1 24

54

130

624

1 53

41

268

2 55

67

932

4 53

055

81

219

-650

4 21

1N

Ox

6 84

0-2

012

395

-335

-91

28 2

241

118

3 67

176

71

745

1 16

62

275

7 69

24

068

498

1 03

9-3

943

132

CO

108

495

-218

987

-1 7

77-5

415

2 77

43

115

9 84

86

038

4 05

14

134

4 17

934

912

10 9

481

494

1 46

1-1

243

7 61

5N

MV

OC

17 0

49-9

617

5-2

58-1

533

118

565

1 48

099

164

076

283

113

868

5 19

834

026

8-1

211

028

Env

ironm

enta

l var

iabl

e \ S

NI c

ode

2930

3132

3334

3536

3740

4145

50-5

255

6061

6263

Oil

3.11

1.16

0.86

0.00

0.63

3.85

0.44

1.48

0.00

3.16

0.00

10.3

19.

982.

974.

541.

141.

926.

53C

oal

0.75

0.27

0.22

0.00

0.20

1.06

0.13

0.36

0.00

3.28

0.00

2.37

1.35

0.42

0.20

0.01

0.03

0.25

Gas

1.64

0.58

0.43

0.00

0.36

1.93

0.19

0.65

0.00

3.31

0.00

2.68

2.57

0.86

0.81

0.08

0.24

0.93

Tota

l fos

sil f

uels

5.50

2.01

1.52

0.00

1.19

6.84

0.75

2.49

0.00

9.75

0.00

15.3

613

.90

4.24

5.54

1.23

2.20

7.72

CO

22

953

278

1 10

6 33

081

1 05

00.

0060

4 55

73

474

566

380

599

1 28

5 09

10.

004

252

037

0.00

6 38

4 77

35

231

304

1 59

6 47

81

672

775

423

265

788

748

3 01

0 84

5C

H4

16 5

837

103

6 25

10.

004

241

21 6

321

881

7 29

80.

0014

296

0.00

26 1

6843

204

52 5

599

500

935

2 42

711

857

N2O

522

199

168

0.00

138

653

6427

10.

0090

00.

001

480

1 94

22

402

399

5110

751

4C

O2e

q3

463

319

1 31

7 22

599

4 50

20.

0073

6 40

34

131

342

439

855

1 52

2 48

00.

004

831

207

0.00

7 39

3 09

96

740

499

3 44

4 94

81

995

846

458

618

872

733

3 41

9 06

2S

O2

12 3

205

930

3 89

70.

002

290

15 2

291

363

6 25

40.

006

332

0.00

16 3

9222

976

6 77

13

424

7 11

41

488

28 9

87N

Ox

9 81

24

296

3 04

90.

001

942

12 3

861

221

5 16

90.

008

197

0.00

24 4

5426

489

9 29

211

331

6 99

03

502

26 5

84C

O25

344

11 0

587

770

0.00

5 62

728

330

3 48

113

268

0.00

23 4

930.

0041

640

45 1

2224

670

9 47

51

420

5 28

618

286

NM

VO

C3

525

1 50

01

111

0.00

924

4 22

148

61

844

0.00

3 62

40.

008

555

9 18

85

140

2 57

138

997

03

827

Env

ironm

enta

l var

iabl

e \ S

NI c

ode

6465

6667

7071

7273

74-7

580

8590

9192

9395

Oil

1.19

0.33

0.20

0.02

7.44

1.19

1.56

1.93

5.05

3.06

4.21

0.00

1.12

1.70

0.48

0.00

Coa

l0.

180.

070.

050.

001.

750.

100.

320.

440.

720.

521.

370.

000.

190.

310.

080.

00G

as0.

320.

110.

070.

002.

430.

220.

500.

631.

290.

891.

900.

000.

340.

490.

120.

00To

tal f

ossi

l fue

ls1.

690.

510.

330.

0211

.62

1.51

2.39

3.01

7.06

4.47

7.48

0.00

1.65

2.50

0.69

0.00

CO

267

7 00

020

2 52

512

9 50

58

758

4 73

0 23

052

3 79

899

3 67

71

167

445

2 61

9 93

11

689

951

2 90

5 54

10.

0061

7 60

493

6 12

924

9 05

60.

00C

H4

5 54

32

336

872

106

69 1

213

555

8 53

39

574

20 1

7621

552

42 2

140.

005

238

15 3

561

727

0.00

N2O

209

7735

41

783

167

314

406

794

850

1 75

80.

0021

993

975

0.00

CO

2eq

858

146

275

438

158

724

12 1

086

734

549

650

333

1 27

0 35

51

494

433

3 28

9 75

42

405

970

4 33

7 03

40.

0079

5 39

31

549

544

308

478

0.00

SO

22

606

813

374

3013

405

2 01

94

208

5 52

97

940

5 66

69

345

0.00

1 97

63

083

738

0.00

NO

x3

283

933

475

3917

575

2 97

94

415

6 11

810

720

7 70

410

895

0.00

2 85

44

065

993

0.00

CO

6 98

42

069

1 12

386

34 4

504

082

9 55

79

658

23 5

6416

005

29 7

870.

005

278

10 4

232

686

0.00

NM

VO

C1

224

388

199

176

890

844

1 73

72

035

4 57

03

270

6 56

00.

001

092

2 10

651

20.

00

Uni

t: TW

h/ye

ar (o

il, c

oal,

gas

and

tota

l fos

sil f

uels

) or t

on/y

ear (

emis

sion

s).


Mai

n co

nsum

ptio

n-ba

sed

resu

lts fo

r all

envi

ronm

enta

l var

iabl

es

Var

iabl

esY

ear a

nd re

visi

on:

1993

a19

94a

1995

a19

96a

1997

a19

98a

1999

a20

00a

2001

a20

02a

2003

a20

00b

2001

b20

02b

2003

b20

04b

2005

bY

ear (

num

eric

al v

alue

):19

9319

9419

9519

9619

9719

9819

9920

0020

0120

0220

0320

0020

0120

0220

0320

0420

05

Econ

omy

Pop

ulat

ion:

8 71

8 56

18

780

745

8 82

6 93

98

840

998

8 84

6 06

28

850

974

8 85

7 87

48

872

109

8 89

5 96

08

924

958

8 95

8 22

98

872

109

8 89

5 96

08

924

958

8 95

8 22

98

993

531

9 02

9 57

2G

DP

:25

2 46

926

2 85

027

3 23

027

7 30

828

5 09

429

6 95

731

0 67

432

4 76

232

8 84

033

6 99

634

4 78

232

4 76

232

8 84

033

6 99

634

4 78

235

9 24

037

0 73

3G

DP

/cap

ita (d

olla

r/cap

ita/y

ear)

:28

958

29 9

3530

954

31 3

6632

228

33 5

5135

073

36 6

0536

965

37 7

5938

488

36 6

0536

965

37 7

5938

488

39 9

4441

058

Dom

estic

fina

l dem

and:

251

157

260

569

267

392

270

561

276

040

289

280

300

470

313

016

313

682

318

663

325

069

313

016

313

682

318

663

325

069

332

008

341

727

Dom

estic

fina

l dem

and/

capi

ta (d

olla

r/cap

ita/y

ear)

:28

807

29 6

7530

293

30 6

0331

205

32 6

8333

921

35 2

8135

261

35 7

0536

287

35 2

8135

261

35 7

0536

287

36 9

1637

845

Exp

orts

:73

077

82 9

5292

289

96 4

1910

9 70

511

9 40

112

8 02

014

3 10

214

4 00

014

5 79

515

1 90

014

3 10

214

4 00

014

5 79

515

1 90

016

8 41

917

9 55

1Im

ports

:71

358

80 3

9186

111

89 1

2210

0 26

311

1 55

311

7 27

413

1 12

412

8 86

612

7 21

013

2 02

713

1 12

412

8 86

612

7 21

013

2 02

714

0 75

915

0 54

4Tr

ade

bala

nce:

1 71

92

562

6 17

87

296

9 44

37

848

10 7

4611

978

15 1

3418

585

19 8

7211

978

15 1

3418

585

19 8

7227

660

29 0

06E

xpor

ts, I

O:1

104

528

124

007

146

980

147

972

166

921

177

449

187

732

213

826

223

717

220

748

225

017

218

087

228

489

225

295

227

946

247

187

266

288

Impo

rts, I

O:1

86 3

8198

265

106

593

103

793

112

889

129

551

136

389

157

096

166

507

161

341

166

076

159

199

170

379

166

464

167

629

175

185

191

246

IO tr

ade

bala

nce:

1 18

147

25 7

4340

387

44 1

7854

032

47 8

9851

343

56 7

3157

210

59 4

0758

941

58 8

8858

110

58 8

3260

316

72 0

0275

042

Tota

l dom

estic

out

put:1

364

491

395

178

429

394

438

004

462

638

484

805

512

468

554

579

576

368

586

103

599

520

561

978

585

435

596

474

610

257

643

556

680

942

Out

put c

ause

d do

mes

tical

ly a

nd a

broa

d du

e to

fina

l dem

and

(incl

. exp

orts

):1

497

503

549

729

604

629

608

287

653

167

697

844

736

668

826

058

875

096

868

912

885

673

840

513

892

113

888

688

896

537

961

920

1 03

4 32

3O

utpu

t cau

sed

dom

estic

ally

and

abr

oad

due

to d

om. f

inal

dem

and:

1 34

6 34

436

9 43

538

9 00

739

3 82

540

8 60

643

6 90

746

1 12

549

7 84

851

9 15

852

6 69

654

0 57

950

3 09

052

7 32

553

7 64

254

9 94

157

1 55

460

5 90

1

Oil

Con

sum

ptio

n-ba

sed

use,

tota

l:15

0.22

156.

0615

3.37

158.

6814

8.64

152.

3115

0.96

146.

8514

3.24

143.

6014

5.04

152.

5214

9.91

150.

4415

4.61

157.

6015

3.59

-

of w

hich

is in

Sw

eden

:53

.55

57.7

053

.93

61.0

554

.12

56.7

054

.31

49.0

449

.41

50.0

852

.82

50.8

551

.43

52.1

756

.02

51.4

251

.10

-

abro

ad (P

PP

):2 27

.67

29.5

230

.28

30.2

230

.40

33.0

535

.80

37.6

037

.43

37.2

137

.09

41.4

742

.08

41.9

643

.46

52.0

452

.87

-

dire

ct u

se:

69.0

068

.84

69.1

667

.42

64.1

162

.55

60.8

560

.21

56.4

056

.30

55.1

360

.21

56.4

056

.30

55.1

354

.14

49.6

2U

se d

ue to

dire

ct im

ports

(PP

P):

18.1

419

.58

21.5

021

.61

22.7

625

.31

26.0

327

.21

28.6

627

.94

28.1

630

.69

31.8

331

.91

34.2

840

.50

43.1

5C

onsu

mpt

ion-

base

d us

e, to

tal/c

apita

(MW

h/ca

p/ye

ar):

2 17

.23

17.7

717

.38

17.9

516

.80

17.2

117

.04

16.5

516

.10

16.0

916

.19

17.1

916

.85

16.8

617

.26

17.5

217

.01

Con

sum

ptio

n-ba

sed

use

(ME

R),

tota

l:3 16

1.04

167.

5316

5.26

170.

6716

0.80

165.

5916

5.51

162.

3515

9.00

159.

6416

1.45

169.

6216

7.63

168.

5217

3.84

181.

2317

8.28

Con

sum

ptio

n-ba

sed

use,

sw

e. in

t., to

tal:

149.

2815

6.15

152.

1115

8.79

146.

8715

0.48

146.

6014

0.69

136.

8213

6.52

139.

3414

5.73

142.

7014

2.45

147.

9314

7.74

142.

23

- of

whi

ch is

abr

oad:

26.7

329

.61

29.0

130

.33

28.6

431

.22

31.4

431

.44

31.0

130

.13

31.3

834

.67

34.8

733

.97

36.7

842

.19

41.5

1In

tens

ity ra

tio (P

PP

):4 1.

041.

001.

041.

001.

061.

061.

141.

201.

211.

241.

181.

201.

211.

241.

181.

231.

27In

tens

ity ra

tio (M

ER

):4 1.

441.

381.

451.

391.

491.

481.

601.

691.

711.

771.

701.

691.

711.

771.

701.

791.

87U

se in

Sw

eden

due

to e

xpor

ts:

39.8

746

.61

48.1

452

.59

53.1

755

.86

54.0

054

.52

56.3

653

.98

60.2

352

.66

54.2

951

.84

57.0

061

.13

60.5

6U

se in

Sw

eden

due

to d

irect

exp

orts

:25

.29

29.1

730

.16

32.4

034

.13

35.8

434

.73

35.7

536

.81

34.8

239

.98

32.8

833

.63

31.8

335

.22

39.7

038

.39

Phy

sica

l tra

de b

alan

ce:5

12.2

017

.08

17.8

722

.37

22.7

722

.81

18.2

016

.92

18.9

316

.77

23.1

411

.20

12.2

19.

8813

.54

9.08

7.69

Phy

sica

l tra

de b

alan

ce, d

irect

:7.

159.

598.

6610

.79

11.3

810

.53

8.70

8.54

8.15

6.88

11.8

22.

201.

81-0

.08

0.94

-0.8

1-4

.76

Pro

duct

ion-

base

d us

e, in

cl. b

unke

rs (S

tatis

tics

Sw

eden

):16

2.42

173.

1517

1.24

181.

0617

1.41

175.

1216

9.16

163.

7716

2.17

160.

3716

8.18

163.

7716

2.17

160.

3716

8.18

166.

7216

1.32

Pro

duct

ion-

base

d us

e, in

cl. b

unke

rs (S

wed

ish

Ene

rgy

Age

ncy)

:14

7.53

153.

7915

4.93

157.

6915

8.22

160.

2715

9.16

155.

5815

3.18

151.

3915

7.67

155.

5815

3.18

151.

3915

7.67

159.

7815

5.03

Coa

lC

onsu

mpt

ion-

base

d us

e, to

tal:

25.9

826

.26

25.4

625

.74

23.1

423

.45

19.9

421

.19

20.2

221

.04

21.6

720

.54

19.8

120

.82

21.2

522

.90

22.7

4

- of

whi

ch is

in S

wed

en:

13.0

612

.82

11.3

013

.76

9.89

10.6

38.

488.

308.

429.

8010

.30

8.29

8.43

9.84

10.3

310

.25

8.04

-

abro

ad (P

PP

):2 12

.93

13.4

414

.16

11.9

813

.25

12.8

211

.46

12.8

911

.79

11.2

411

.37

12.2

511

.38

10.9

810

.92

12.6

514

.70

-

dire

ct u

se:

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

0.00

Use

due

to d

irect

impo

rts (P

PP

):7.

027.

809.

528.

849.

789.

247.

718.

968.

518.

318.

968.

908.

458.

288.

829.

0811

.30

Con

sum

ptio

n-ba

sed

use,

tota

l/cap

ita (M

Wh/

cap/

year

):2

2.98

2.99

2.88

2.91

2.62

2.65

2.25

2.39

2.27

2.36

2.42

2.32

2.23

2.33

2.37

2.55

2.52

Con

sum

ptio

n-ba

sed

use

(ME

R),

tota

l:3 31

.04

31.4

831

.02

30.4

928

.44

28.6

024

.59

26.5

025

.18

25.8

826

.70

25.5

924

.60

25.5

526

.08

28.6

529

.61

Con

sum

ptio

n-ba

sed

use,

sw

e. in

t., to

tal:

19.2

919

.52

17.6

620

.33

16.0

417

.05

13.2

014

.16

14.1

415

.94

16.4

013

.86

13.9

515

.84

16.1

916

.46

14.2

8

- of

whi

ch is

abr

oad:

6.23

6.70

6.36

6.57

6.14

6.42

4.72

5.86

5.72

6.14

6.11

5.57

5.52

6.00

5.86

6.21

6.24

Inte

nsity

ratio

(PP

P):4

2.07

2.01

2.23

1.82

2.16

2.00

2.43

2.20

2.06

1.83

1.86

2.20

2.06

1.83

1.86

2.04

2.36

Inte

nsity

ratio

(ME

R):4

2.88

2.78

3.10

2.55

3.02

2.80

3.41

3.11

2.93

2.62

2.69

3.11

2.93

2.62

2.69

2.96

3.46

Use

in S

wed

en d

ue to

exp

orts

:7.

197.

767.

959.

018.

068.

275.

876.

977.

428.

028.

206.

997.

417.

988.

168.

578.

89U

se in

Sw

eden

due

to d

irect

exp

orts

:3.

683.

994.

414.

814.

714.

783.

194.

064.

394.

614.

654.

094.

414.

624.

704.

965.

79P

hysi

cal t

rade

bal

ance

:5 -5

.73

-5.6

8-6

.22

-2.9

6-5

.19

-4.5

5-5

.59

-5.9

2-4

.37

-3.2

2-3

.18

-5.2

7-3

.97

-3.0

0-2

.75

-4.0

9-5

.81

Phy

sica

l tra

de b

alan

ce, d

irect

:-3

.35

-3.8

1-5

.11

-4.0

3-5

.06

-4.4

6-4

.52

-4.9

0-4

.13

-3.7

0-4

.31

-4.8

1-4

.04

-3.6

6-4

.12

-4.1

2-5

.51

Pro

duct

ion-

base

d us

e, in

cl. b

unke

rs (S

tatis

tics

Sw

eden

):20

.25

20.5

819

.24

22.7

717

.95

18.9

114

.35

15.2

715

.84

17.8

218

.50

15.2

715

.84

17.8

218

.50

18.8

216

.93

Pro

duct

ion-

base

d us

e, in

cl. b

unke

rs (S

wed

ish

Ene

rgy

Age

ncy)

:2.

802.

842.

923.

143.

243.

253.

633.

543.

973.

754.

463.

543.

973.

754.

464.

624.

54

Appendix G Excel tables 113Y

ear a

nd re

visi

on:

1993

a19

94a

1995

a19

96a

1997

a19

98a

1999

a20

00a

2001

a20

02a

2003

a20

00b

2001

b20

02b

2003

b20

04b

2005

bY

ear (

num

eric

al v

alue

):19

9319

9419

9519

9619

9719

9819

9920

0020

0120

0220

0320

0020

0120

0220

0320

0420

05

Gas

Con

sum

ptio

n-ba

sed

use,

tota

l:35

.40

36.9

937

.04

37.0

136

.97

36.5

536

.30

37.7

036

.78

38.0

337

.84

37.2

436

.76

38.2

037

.61

41.8

942

.41

-

of w

hich

is in

Sw

eden

:9.

429.

439.

429.

269.

0811

.32

10.7

58.

9910

.36

11.1

810

.68

9.03

10.3

711

.26

10.7

210

.61

9.96

-

abro

ad (P

PP

):2 24

.90

26.4

426

.41

26.4

026

.60

23.7

524

.04

27.3

624

.80

25.4

325

.42

26.8

624

.77

25.5

425

.16

28.9

530

.15

-

dire

ct u

se:

1.08

1.12

1.21

1.35

1.28

1.47

1.51

1.35

1.62

1.41

1.73

1.35

1.62

1.41

1.73

2.33

2.31

Use

due

to d

irect

impo

rts (P

PP

):20

.36

21.3

020

.77

21.5

720

.09

17.3

917

.96

21.3

719

.70

21.5

923

.17

21.4

019

.80

21.7

122

.74

23.7

727

.07

Con

sum

ptio

n-ba

sed

use,

tota

l/cap

ita (M

Wh/

cap/

year

):2

4.06

4.21

4.20

4.19

4.18

4.13

4.10

4.25

4.13

4.26

4.22

4.20

4.13

4.28

4.20

4.66

4.70

Con

sum

ptio

n-ba

sed

use

(ME

R),

tota

l:3 45

.14

47.2

647

.41

47.4

847

.61

46.0

946

.07

48.9

847

.23

48.9

949

.08

48.3

147

.19

49.2

148

.74

55.0

356

.49

Con

sum

ptio

n-ba

sed

use,

sw

e. in

t., to

tal:

19.0

019

.49

19.1

619

.24

19.3

621

.01

20.3

818

.76

20.7

821

.52

20.9

618

.65

20.7

821

.63

20.9

123

.39

23.2

3

- of

whi

ch is

abr

oad:

8.49

8.93

8.53

8.64

8.99

8.22

8.12

8.42

8.80

8.93

8.54

8.27

8.79

8.96

8.45

10.4

510

.97

Inte

nsity

ratio

(PP

P):4

2.93

2.96

3.10

3.06

2.96

2.89

2.96

3.25

2.82

2.85

2.98

3.25

2.82

2.85

2.98

2.77

2.75

Inte

nsity

ratio

(ME

R):4

4.08

4.11

4.31

4.27

4.14

4.05

4.17

4.59

4.00

4.08

4.29

4.59

4.00

4.08

4.29

4.03

4.03

Use

in S

wed

en d

ue to

exp

orts

:10

.64

10.4

610

.22

11.1

411

.67

9.88

10.6

611

.59

12.6

212

.35

11.9

011

.55

12.6

112

.28

11.8

613

.49

14.4

5U

se in

Sw

eden

due

to d

irect

exp

orts

:7.

347.

016.

587.

447.

736.

287.

058.

008.

628.

277.

968.

038.

708.

338.

069.

5410

.65

Phy

sica

l tra

de b

alan

ce:5

-14.

26-1

5.98

-16.

19-1

5.26

-14.

93-1

3.88

-13.

38-1

5.77

-12.

18-1

3.08

-13.

53-1

5.31

-12.

16-1

3.26

-13.

30-1

5.46

-15.

69P

hysi

cal t

rade

bal

ance

, dire

ct:

-13.

02-1

4.29

-14.

19-1

4.13

-12.

36-1

1.12

-10.

91-1

3.37

-11.

08-1

3.32

-15.

21-1

3.36

-11.

10-1

3.38

-14.

68-1

4.24

-16.

42P

rodu

ctio

n-ba

sed

use,

incl

. bun

kers

(Sta

tistic

s S

wed

en):

21.1

521

.01

20.8

521

.75

22.0

422

.67

22.9

221

.93

24.6

024

.95

24.3

121

.93

24.6

024

.95

24.3

126

.43

26.7

2P

rodu

ctio

n-ba

sed

use,

incl

. bun

kers

(Sw

edis

h E

nerg

y A

genc

y):

14.7

015

.12

15.7

716

.00

15.3

215

.01

14.5

515

.61

16.6

717

.20

17.1

015

.61

16.6

717

.20

17.1

017

.33

16.3

5

Tota

l fos

sil f

uels

Con

sum

ptio

n-ba

sed

use,

tota

l:21

1.61

219.

3121

5.87

221.

4220

8.74

212.

3120

7.20

205.

7420

0.24

202.

6620

4.55

210.

3020

6.48

209.

4621

3.47

222.

3921

8.75

-

of w

hich

is in

Sw

eden

:76

.03

79.9

574

.65

84.0

673

.09

78.6

673

.54

66.3

368

.19

71.0

673

.80

68.1

770

.24

73.2

777

.07

72.2

869

.10

-

abro

ad (P

PP

):2 65

.50

69.4

070

.85

68.6

070

.26

69.6

271

.30

77.8

574

.02

73.8

973

.89

80.5

878

.22

78.4

879

.54

93.6

597

.72

-

dire

ct u

se:

70.0

869

.96

70.3

768

.76

65.4

064

.03

62.3

661

.55

58.0

257

.71

56.8

661

.55

58.0

257

.71

56.8

656

.46

51.9

2U

se d

ue to

dire

ct im

ports

(PP

P):

45.5

248

.67

51.7

952

.02

52.6

251

.95

51.6

957

.54

56.8

757

.84

60.2

960

.99

60.0

761

.89

65.8

573

.36

81.5

3C

onsu

mpt

ion-

base

d us

e, to

tal/c

apita

(MW

h/ca

p/ye

ar):

2 24

.27

24.9

824

.46

25.0

523

.60

23.9

923

.39

23.1

922

.51

22.7

122

.83

23.7

023

.21

23.4

723

.83

24.7

324

.23

Con

sum

ptio

n-ba

sed

use

(ME

R),

tota

l:3 23

7.22

246.

2724

3.69

248.

6423

6.86

240.

2823

6.17

237.

8323

1.40

234.

5023

7.24

243.

5223

9.42

243.

2824

8.66

264.

9126

4.37

Con

sum

ptio

n-ba

sed

use,

sw

e. in

t., to

tal:

187.

5719

5.16

188.

9219

8.37

182.

2718

8.54

180.

1817

3.61

171.

7517

3.98

176.

7017

8.23

177.

4317

9.92

185.

0218

7.59

179.

74

- of

whi

ch is

abr

oad:

41.4

645

.25

43.9

045

.54

43.7

845

.86

44.2

745

.72

45.5

445

.20

46.0

348

.51

49.1

848

.94

51.0

958

.84

58.7

2In

tens

ity ra

tio (P

PP

):4,6

1.58

1.53

1.61

1.51

1.60

1.52

1.61

1.70

1.63

1.63

1.61

1.66

1.59

1.60

1.56

1.59

1.66

Inte

nsity

ratio

(ME

R):4,

6 2.

202.

132.

252.

102.

252.

132.

262.

402.

312.

342.

322.

352.

262.

292.

252.

312.

44U

se in

Sw

eden

due

to e

xpor

ts:

57.7

164

.83

66.3

172

.75

72.9

174

.01

70.5

373

.09

76.4

074

.35

80.3

371

.20

74.3

072

.09

77.0

283

.18

83.9

0U

se in

Sw

eden

due

to d

irect

exp

orts

:36

.31

40.1

741

.14

44.6

546

.58

46.9

044

.96

47.8

049

.82

47.7

052

.59

45.0

146

.74

44.7

747

.98

54.2

054

.84

Phy

sica

l tra

de b

alan

ce:5

-7.7

8-4

.58

-4.5

44.

152.

654.

39-0

.77

-4.7

62.

370.

476.

44-9

.38

-3.9

3-6

.38

-2.5

2-1

0.47

-13.

82P

hysi

cal t

rade

bal

ance

, dire

ct:

-9.2

2-8

.51

-10.

64-7

.36

-6.0

4-5

.05

-6.7

3-9

.73

-7.0

5-1

0.14

-7.7

0-1

5.98

-13.

33-1

7.12

-17.

87-1

9.16

-26.

69P

rodu

ctio

n-ba

sed

use,

incl

. bun

kers

(Sta

tistic

s S

wed

en):

203.

8221

4.74

211.

3322

5.57

211.

4021

6.69

206.

4320

0.97

202.

6120

3.13

210.

9920

0.97

202.

6120

3.13

210.

9921

1.96

204.

97P

rodu

ctio

n-ba

sed

use,

incl

. bun

kers

(Sw

edis

h E

nerg

y A

genc

y):

165.

0217

1.75

173.

6217

6.82

176.

7817

8.53

177.

3417

4.73

173.

8217

2.33

179.

2317

4.73

173.

8217

2.33

179.

2318

1.72

175.

92

CO

2C

onsu

mpt

ion-

base

d em

issi

ons,

tota

l:69

270

919

71 4

42 3

5671

258

184

71 6

54 6

2768

203

098

71 2

94 3

5570

625

908

71 3

63 1

0969

605

738

70 8

88 3

6272

546

818

73 0

28 9

9672

085

043

73 3

72 5

0175

871

499

80 5

05 3

2680

358

841

-

of w

hich

is in

Sw

eden

:23

059

794

24 0

67 5

9422

741

874

25 0

77 7

3122

101

061

23 6

40 5

9822

326

899

20 3

77 7

8420

920

699

21 7

92 9

4322

910

628

20 8

27 7

9121

371

963

22 3

44 8

5423

775

151

22 7

15 4

3022

014

454

-

abro

ad (P

PP

):2 27

688

591

28 9

00 1

5629

966

906

28 4

70 2

4528

881

582

30 8

07 4

3931

911

945

34 8

07 2

0133

488

761

34 0

14 9

5634

858

118

36 0

23 0

8135

516

802

35 9

47 1

8437

318

277

43 2

53 9

4845

026

111

-

dire

ct u

se:

18 5

22 5

3418

474

605

18 5

49 4

0418

106

651

17 2

20 4

5616

846

319

16 3

87 0

6316

178

124

15 1

96 2

7815

080

463

14 7

78 0

7116

178

124

15 1

96 2

7815

080

463

14 7

78 0

7114

535

948

13 3

18 2

77E

mis

sion

s du

e to

dire

ct im

ports

(PP

P):

18 3

24 7

8019

679

536

21 3

68 1

0321

269

774

21 8

16 0

2723

460

856

23 3

40 2

8225

509

140

25 6

81 5

7326

081

577

27 1

32 6

3527

210

587

27 2

42 3

4327

950

119

29 9

57 6

6233

629

090

36 6

17 3

03C

onsu

mpt

ion-

base

d em

issi

ons,

tota

l/cap

ita (t

on/c

ap/y

ear)

:2 7.

958.

148.

078.

107.

718.

057.

978.

047.

827.

948.

108.

238.

108.

228.

478.

958.

90C

onsu

mpt

ion-

base

d em

issi

ons

(ME

R),

tota

l:3 80

097

999

82 6

65 0

2683

021

726

82 9

47 8

2179

760

511

83 6

74 1

5283

591

690

85 7

10 7

6583

705

218

85 5

47 3

3087

967

043

87 8

77 8

4287

038

371

88 8

64 1

7592

380

028

100

143

224

101

381

058

Con

sum

ptio

n-ba

sed

emis

sion

s, s

we.

int.,

tota

l:55

267

728

57 3

51 2

7555

999

876

57 8

99 4

9253

490

947

55 6

97 6

9953

484

313

51 9

76 9

6251

213

411

51 9

86 1

7853

393

430

52 9

65 6

5552

578

897

53 3

96 5

7455

366

335

56 3

15 7

0854

124

675

-

of w

hich

is a

broa

d:13

685

400

14 8

09 0

7614

708

598

14 7

15 1

1014

169

430

15 2

10 7

8214

770

350

15 4

21 0

5415

096

434

15 1

12 7

7215

704

730

15 9

59 7

4016

010

657

15 9

71 2

5616

813

113

19 0

64 3

3018

791

945

Inte

nsity

ratio

(PP

P):4

2.02

1.95

2.04

1.93

2.04

2.03

2.16

2.26

2.22

2.25

2.22

2.26

2.22

2.25

2.22

2.27

2.40

Inte

nsity

ratio

(ME

R):4

2.81

2.71

2.84

2.70

2.85

2.84

3.04

3.19

3.15

3.22

3.20

3.19

3.15

3.22

3.20

3.30

3.51

Em

issi

ons

in S

wed

en d

ue to

exp

orts

:19

120

930

21 3

53 7

9822

106

565

23 8

43 6

9823

730

338

24 2

94 3

8823

141

704

23 8

85 4

2124

979

688

24 4

99 6

5126

215

609

23 4

22 9

7924

513

915

23 9

33 9

0725

341

427

27 6

94 6

5127

419

284

Em

issi

ons

in S

wed

en d

ue to

dire

ct e

xpor

ts:

11 8

22 1

6713

047

903

13 4

65 8

4814

520

269

14 9

31 9

4215

314

942

14 6

52 2

9715

418

275

16 1

52 2

4415

539

389

16 8

31 4

9614

721

484

15 4

22 6

0714

834

426

15 6

71 3

5417

717

097

17 6

34 1

12P

hysi

cal t

rade

bal

ance

:5 -8

567

660

-7 5

46 3

58-7

860

341

-4 6

26 5

47-5

151

244

-6 5

13 0

51-8

770

241

-10

921

780

-8 5

09 0

74-9

515

306

-8 6

42 5

09-1

2 60

0 10

2-1

1 00

2 88

6-1

2 01

3 27

7-1

1 97

6 85

0-1

5 55

9 29

7-1

7 60

6 82

7P

hysi

cal t

rade

bal

ance

, dire

ct:

-6 5

02 6

12-6

631

633

-7 9

02 2

55-6

749

505

-6 8

84 0

84-8

145

914

-8 6

87 9

86-1

0 09

0 86

6-9

529

329

-10

542

188

-10

301

140

-12

489

103

-11

819

736

-13

115

693

-14

286

308

-15

911

993

-18

983

190

Pro

duct

ion-

base

d em

issi

ons,

incl

. bun

kers

(Sta

tistic

s S

wed

en):

60 7

03 3

0563

895

997

63 3

97 8

4367

028

080

63 0

51 8

5564

781

305

61 8

55 6

6660

441

329

61 0

96 6

6561

373

057

63 9

04 3

0960

441

329

61 0

96 6

6561

373

057

63 9

04 3

0964

956

079

62 7

62 1

35P

rodu

ctio

n-ba

sed

emis

sion

s, e

xcl.

bunk

ers

(UN

FCC

C):

56 6

09 1

6459

122

083

58 5

43 7

4262

043

940

57 3

89 6

5658

091

130

55 1

80 2

9753

913

489

54 6

69 1

3355

714

084

56 4

00 4

9553

913

489

54 6

69 1

3355

714

084

56 4

00 4

9555

785

642

53 1

86 6

34

114 Excel tables Appendix GY

ear a

nd re

visi

on:

1993

a19

94a

1995

a19

96a

1997

a19

98a

1999

a20

00a

2001

a20

02a

2003

a20

00b

2001

b20

02b

2003

b20

04b

2005

bY

ear (

num

eric

al v

alue

):19

9319

9419

9519

9619

9719

9819

9920

0020

0120

0220

0320

0020

0120

0220

0320

0420

05

CH

4C

onsu

mpt

ion-

base

d em

issi

ons,

tota

l:92

0 08

091

8 98

392

6 03

485

9 97

586

5 88

396

1 89

898

0 85

097

8 90

81

011

835

1 06

0 06

81

031

452

958

094

997

731

1 04

9 53

21

020

682

1 20

1 09

91

235

599

-

of w

hich

is in

Sw

eden

:25

7 21

824

6 47

623

7 27

222

4 39

921

0 11

822

1 38

621

7 52

620

5 76

619

7 49

919

5 97

118

8 35

820

8 33

820

0 16

519

8 95

719

0 73

019

8 58

819

2 47

4

- ab

road

(PP

P):2

648

595

658

651

674

330

620

910

641

900

726

974

750

952

760

687

802

403

851

901

830

727

737

302

785

632

838

378

817

585

990

218

1 03

0 22

3

- di

rect

use

:14

267

13 8

5614

432

14 6

6613

866

13 5

3812

372

12 4

5411

933

12 1

9712

367

12 4

5411

933

12 1

9712

367

12 2

9312

902

Em

issi

ons

due

to d

irect

impo

rts (P

PP

):31

9 00

132

7 60

032

9 89

132

3 33

834

8 55

537

0 59

238

7 88

338

1 20

743

0 98

947

2 73

045

0 04

335

8 47

940

5 80

445

3 79

642

2 16

047

5 25

552

5 17

6C

onsu

mpt

ion-

base

d em

issi

ons,

tota

l/cap

ita (k

g/ca

p/ye

ar):

2 10

610

510

597

9810

911

111

011

411

911

510

811

211

811

413

413

7C

onsu

mpt

ion-

base

d em

issi

ons

(ME

R),

tota

l:3 1

173

700

1 17

4 75

41

190

743

1 10

6 27

01

122

749

1 25

4 02

91

285

960

1 29

2 46

61

349

664

1 42

7 20

11

398

941

1 26

2 01

31

328

499

1 41

0 83

71

382

358

1 65

0 67

11

716

599

Con

sum

ptio

n-ba

sed

emis

sion

s, s

we.

int.,

tota

l:39

3 85

638

1 78

637

2 88

235

2 72

033

9 57

536

2 24

435

9 47

534

7 10

034

4 76

034

5 06

033

0 74

634

5 70

934

4 59

834

5 87

333

1 06

236

2 60

435

8 79

8

- of

whi

ch is

abr

oad:

122

371

121

454

121

178

113

655

115

591

127

320

129

578

128

879

135

329

136

892

130

021

124

917

132

500

134

719

127

964

151

723

153

422

Inte

nsity

ratio

(PP

P):4

5.30

5.42

5.56

5.46

5.55

5.71

5.80

5.90

5.93

6.22

6.39

5.90

5.93

6.22

6.39

6.53

6.71

Inte

nsity

ratio

(ME

R):4

7.37

7.53

7.75

7.63

7.78

8.00

8.15

8.34

8.43

8.91

9.22

8.34

8.43

8.91

9.22

9.49

9.85

Em

issi

ons

in S

wed

en d

ue to

exp

orts

:54

162

61 6

3866

362

77 4

9089

891

72 1

0969

093

72 5

3880

305

72 8

1873

256

69 9

6577

637

69 8

3070

883

64 0

8463

500

Em

issi

ons

in S

wed

en d

ue to

dire

ct e

xpor

ts:

19 7

2422

815

22 2

1931

423

38 8

7321

571

18 7

1020

705

25 0

1421

221

24 2

4520

167

24 3

2320

919

23 4

3113

484

12 7

85P

hysi

cal t

rade

bal

ance

:5 -5

94 4

33-5

97 0

13-6

07 9

68-5

43 4

20-5

52 0

08-6

54 8

65-6

81 8

59-6

88 1

50-7

22 0

98-7

79 0

82-7

57 4

71-6

67 3

37-7

07 9

96-7

68 5

48-7

46 7

02-9

26 1

34-9

66 7

23P

hysi

cal t

rade

bal

ance

, dire

ct:

-299

277

-304

784

-307

672

-291

915

-309

682

-349

021

-369

173

-360

502

-405

975

-451

508

-425

798

-338

311

-381

481

-432

877

-398

729

-461

770

-512

391

Pro

duct

ion-

base

d em

issi

ons,

incl

. bun

kers

(Sta

tistic

s S

wed

en):

325

647

321

970

318

066

316

555

313

875

307

033

298

991

290

758

289

737

280

986

273

981

290

758

289

737

280

986

273

981

274

965

268

876

Pro

duct

ion-

base

d em

issi

ons,

exc

l. bu

nker

s (U

NFC

CC

):34

0 03

133

6 40

033

2 28

433

0 65

432

7 84

531

9 96

031

2 78

930

4 16

530

2 73

429

4 26

328

7 72

230

4 16

530

2 73

429

4 26

328

7 72

228

8 75

128

2 73

8

N2O

Con

sum

ptio

n-ba

sed

emis

sion

s, to

tal:

46 4

8546

567

46 1

6143

054

42 8

5847

515

46 3

7345

862

45 8

1347

485

45 5

0545

103

45 3

6547

260

45 3

0052

294

52 5

03

- of

whi

ch is

in S

wed

en:

19 8

8419

351

18 4

4817

572

15 9

0917

267

16 6

8215

972

15 1

0615

493

15 1

3516

192

15 3

9315

752

15 3

9815

945

15 5

27

- ab

road

(PP

P):2

25 4

0626

120

26 4

7524

210

25 6

6728

993

28 4

7228

689

29 5

9330

860

29 1

9727

710

28 8

5930

378

28 7

2935

162

35 8

55

- di

rect

use

:1

194

1 09

61

238

1 27

21

282

1 25

51

219

1 20

11

114

1 13

11

173

1 20

11

114

1 13

11

173

1 18

71

121

Em

issi

ons

due

to d

irect

impo

rts (P

PP

):14

609

15 1

5715

386

14 7

9216

314

17 2

3817

287

17 2

8618

921

19 7

8917

878

16 2

4717

621

18 6

5217

059

19 3

7220

675

Con

sum

ptio

n-ba

sed

emis

sion

s, to

tal/c

apita

(kg/

cap/

year

):2

5.33

5.30

5.23

4.87

4.84

5.37

5.24

5.17

5.15

5.32

5.08

5.08

5.10

5.30

5.06

5.81

5.81

Con

sum

ptio

n-ba

sed

emis

sion

s (M

ER

), to

tal:3

56 4

1956

710

56 5

5452

657

53 1

2959

165

57 9

4157

687

58 2

7260

784

58 4

2156

526

57 5

1660

352

58 0

0968

257

69 2

44C

onsu

mpt

ion-

base

d em

issi

ons,

sw

e. in

t., to

tal:

35 9

7035

310

34 1

8732

525

31 1

8034

114

33 0

3832

482

31 6

0732

334

31 2

8932

180

31 5

1232

346

31 3

1234

832

34 3

22

- of

whi

ch is

abr

oad:

14 8

9114

864

14 5

0113

681

13 9

8915

592

15 1

3815

309

15 3

8615

709

14 9

8114

787

15 0

0515

464

14 7

4117

700

17 6

74In

tens

ity ra

tio (P

PP

):4 1.

711.

761.

831.

771.

831.

861.

881.

871.

921.

961.

951.

871.

921.

961.

951.

992.

03In

tens

ity ra

tio (M

ER

):4 2.

372.

442.

542.

472.

572.

612.

652.

652.

732.

812.

812.

652.

732.

812.

812.

892.

98E

mis

sion

s in

Sw

eden

due

to e

xpor

ts:

6 68

17

535

7 86

99

125

10 4

749

217

8 40

58

884

9 30

98

606

8 91

38

664

9 02

28

347

8 65

08

041

8 01

1E

mis

sion

s in

Sw

eden

due

to d

irect

exp

orts

:3

620

4 02

63

937

4 90

55

768

4 76

34

182

4 54

24

718

4 18

94

543

4 44

44

591

4 09

84

409

3 44

13

356

Phy

sica

l tra

de b

alan

ce:5

-18

726

-18

585

-18

606

-15

085

-15

193

-19

776

-20

067

-19

805

-20

284

-22

255

-20

284

-19

046

-19

836

-22

030

-20

079

-27

121

-27

844

Phy

sica

l tra

de b

alan

ce, d

irect

:-1

0 98

9-1

1 13

1-1

1 45

0-9

888

-10

546

-12

476

-13

105

-12

744

-14

203

-15

600

-13

335

-11

803

-13

031

-14

554

-12

650

-15

931

-17

319

Pro

duct

ion-

base

d em

issi

ons,

incl

. bun

kers

(Sta

tistic

s S

wed

en):

27 7

5927

982

27 5

5527

969

27 6

6527

739

26 3

0626

057

25 5

2925

230

25 2

2126

057

25 5

2925

230

25 2

2125

173

24 6

59P

rodu

ctio

n-ba

sed

emis

sion

s, e

xcl.

bunk

ers

(UN

FCC

C):

26 6

8426

880

26 4

3526

844

26 5

5226

506

25 0

8524

842

24 3

0724

046

23 9

7624

842

24 3

0724

046

23 9

7623

907

23 4

31

CO

2eq

7

Con

sum

ptio

n-ba

sed

emis

sion

s, to

tal:

103

002

857

105

176

816

105

014

785

103

060

791

99 6

72 5

7610

6 22

3 82

310

5 59

9 30

910

6 13

7 29

910

5 05

6 34

110

7 87

0 03

610

8 31

3 97

810

7 13

1 03

510

7 10

0 68

511

0 06

3 39

411

1 34

8 77

012

1 93

9 38

612

2 58

2 43

6

- of

whi

ch is

in S

wed

en:

34 6

25 5

3535

242

361

33 4

43 3

5235

237

384

31 4

45 3

2533

642

576

32 0

66 2

9029

650

155

29 7

51 1

6430

711

250

31 5

58 0

2830

222

550

30 3

47 2

1831

405

947

32 5

53 9

0131

828

665

30 8

69 9

11

- ab

road

(PP

P):2

49 1

85 0

4150

829

113

52 3

35 1

7749

014

450

50 3

18 1

8955

061

580

56 5

08 2

5459

675

176

59 5

12 9

6661

471

576

61 3

54 5

4260

096

517

60 9

61 2

5562

970

236

63 3

93 4

6174

948

650

77 7

75 7

97

- di

rect

use

:19

192

281

19 1

05 3

4119

236

256

18 8

08 9

5717

909

062

17 5

19 6

6717

024

765

16 8

11 9

6815

792

211

15 6

87 2

1015

401

408

16 8

11 9

6815

792

211

15 6

87 2

1015

401

408

15 1

62 0

7113

936

729

Em

issi

ons

due

to d

irect

impo

rts (P

PP

):29

552

460

31 2

57 6

4633

065

590

32 6

45 4

8034

193

012

36 5

87 1

3236

844

666

38 8

73 2

7540

597

784

42 1

43 4

3542

125

757

39 7

75 1

7441

226

862

43 2

61 8

2444

111

278

49 6

14 8

9654

055

187

Con

sum

ptio

n-ba

sed

emis

sion

s, to

tal/c

apita

(ton

/cap

/yea

r):2

11.8

111

.98

11.9

011

.66

11.2

712

.00

11.9

211

.96

11.8

112

.09

12.0

912

.08

12.0

412

.33

12.4

313

.56

13.5

8C

onsu

mpt

ion-

base

d em

issi

ons

(ME

R),

tota

l:3 12

2 23

5 70

312

4 91

5 06

112

5 55

9 01

612

2 50

3 18

411

9 80

8 18

012

8 35

0 00

912

8 55

8 54

013

0 73

5 62

613

0 11

2 56

413

4 36

1 61

513

5 45

5 45

713

1 90

3 04

013

2 76

6 66

813

7 20

0 83

013

9 39

2 20

815

5 96

7 12

315

8 89

5 13

5C

onsu

mpt

ion-

base

d em

issi

ons,

sw

e. in

t., to

tal:

74 6

89 2

6076

315

026

74 4

28 2

3375

389

289

70 2

87 7

5973

880

303

71 2

75 2

2269

335

427

68 2

51 4

8569

255

896

70 0

38 7

0270

201

379

69 5

84 0

4770

687

298

72 0

25 2

3374

728

202

72 2

99 3

73

- of

whi

ch is

abr

oad:

20 8

71 4

4421

967

323

21 7

48 6

2521

342

948

20 9

33 3

7222

718

060

22 1

84 1

6722

873

305

22 7

08 1

1022

857

436

23 0

79 2

6623

166

861

23 4

44 6

1723

594

141

24 0

69 9

2427

737

467

27 4

92 7

33In

tens

ity ra

tio (P

PP

):4,6

2.36

2.31

2.41

2.30

2.40

2.42

2.55

2.61

2.62

2.69

2.66

2.59

2.60

2.67

2.63

2.70

2.83

Inte

nsity

ratio

(ME

R):4,

6 3.

283.

213.

353.

213.

373.

403.

583.

683.

723.

853.

833.

663.

693.

823.

803.

934.

15E

mis

sion

s in

Sw

eden

due

to e

xpor

ts:

22 3

29 3

1924

984

084

25 9

39 6

7128

299

784

28 8

64 9

9328

665

845

27 1

98 2

8228

162

794

29 5

51 7

5628

696

603

30 5

16 9

8427

577

943

28 9

41 1

5227

988

030

29 5

11 4

3131

533

188

31 2

36 0

61E

mis

sion

s in

Sw

eden

due

to d

irect

exp

orts

:13

358

506

14 7

74 9

6415

152

882

16 7

00 6

2717

536

471

17 2

44 3

5516

341

583

17 2

61 1

4618

140

016

17 2

83 5

1518

748

908

16 5

22 4

9217

356

453

16 5

44 0

2017

530

096

19 0

66 9

8718

943

033

Phy

sica

l tra

de b

alan

ce:5

-26

855

721

-25

845

029

-26

395

505

-20

714

666

-21

453

196

-26

395

735

-29

309

972

-31

512

382

-29

961

210

-32

774

974

-30

837

559

-32

518

574

-32

020

103

-34

982

206

-33

882

031

-43

415

462

-46

539

736

Phy

sica

l tra

de b

alan

ce, d

irect

:-1

6 19

3 95

4-1

6 48

2 68

2-1

7 91

2 70

8-1

5 94

4 85

3-1

6 65

6 54

1-1

9 34

2 77

7-2

0 50

3 08

3-2

1 61

2 12

9-2

2 45

7 76

8-2

4 85

9 91

9-2

3 37

6 84

9-2

3 25

2 68

3-2

3 87

0 40

9-2

6 71

7 80

4-2

6 58

1 18

2-3

0 54

7 90

9-3

5 11

2 15

4P

rodu

ctio

n-ba

sed

emis

sion

s, in

cl. b

unke

rs (S

tatis

tics

Sw

eden

):76

147

182

79 3

31 7

8778

619

279

82 3

46 1

2578

219

380

79 8

28 0

8876

289

337

74 6

24 9

1775

095

132

75 0

95 0

6377

476

420

74 6

24 9

1775

095

132

75 0

95 0

6377

476

420

78 5

33 9

7476

052

821

Pro

duct

ion-

base

d em

issi

ons,

exc

l. bu

nker

s (U

NFC

CC

):72

021

864

74 5

19 2

2673

716

479

77 3

09 1

7672

505

666

73 0

27 2

7869

525

073

68 0

01 8

3768

561

686

69 3

47 9

9269

875

150

68 0

01 8

3768

561

686

69 3

47 9

9269

875

150

69 2

60 6

1366

387

764

Appendix G Excel tables 115Y

ear a

nd re

visi

on:

1993

a19

94a

1995

a19

96a

1997

a19

98a

1999

a20

00a

2001

a20

02a

2003

a20

00b

2001

b20

02b

2003

b20

04b

2005

bY

ear (

num

eric

al v

alue

):19

9319

9419

9519

9619

9719

9819

9920

0020

0120

0220

0320

0020

0120

0220

0320

0420

05

SO2

Con

sum

ptio

n-ba

sed

emis

sion

s, to

tal:

223

817

223

431

208

188

195

143

173

029

171

270

158

904

144

971

136

892

139

622

130

774

220

414

219

525

217

480

230

226

255

992

251

821

-

of w

hich

is in

Sw

eden

:39

658

38 9

6731

755

32 0

1327

147

28 4

3924

005

18 7

1017

756

18 1

9020

367

22 8

8722

579

22 2

1826

035

22 3

2221

824

-

abro

ad (P

PP

):2 17

7 48

917

8 19

617

0 97

015

8 90

514

2 24

613

9 38

713

1 84

212

3 72

711

7 06

311

9 51

810

8 58

119

4 99

219

4 87

219

3 34

920

2 36

623

1 99

822

8 65

3

- di

rect

use

:6

670

6 26

85

462

4 22

53

637

3 44

33

057

2 53

52

073

1 91

41

826

2 53

52

073

1 91

41

826

1 67

21

344

Em

issi

ons

due

to d

irect

impo

rts (P

PP

):16

6 65

517

4 98

118

4 12

216

8 60

317

5 56

619

0 90

716

3 41

614

4 79

416

0 25

515

0 97

613

8 80

218

3 98

618

9 67

818

7 13

520

3 78

823

0 60

223

6 50

6C

onsu

mpt

ion-

base

d em

issi

ons,

tota

l/cap

ita (k

g/ca

p/ye

ar):

2 25

.67

25.4

523

.59

22.0

719

.56

19.3

517

.94

16.3

415

.39

15.6

414

.60

24.8

424

.68

24.3

725

.70

28.4

627

.89

Con

sum

ptio

n-ba

sed

emis

sion

s (M

ER

), to

tal:3

293

220

292

629

275

302

258

175

229

951

227

282

212

471

195

972

186

178

191

129

178

807

300

790

301

570

300

805

319

747

361

323

358

576

Con

sum

ptio

n-ba

sed

emis

sion

s, s

we.

int.,

tota

l:78

099

79 1

6966

935

63 9

1656

405

57 5

9950

318

41 9

6839

557

38 5

9342

684

58 0

8257

494

54 0

4366

052

70 2

1767

814

-

of w

hich

is a

broa

d:31

771

33 9

3329

718

27 6

7825

621

25 7

1723

256

20 7

2419

728

18 4

9020

492

32 6

6032

841

29 9

1138

191

46 2

2344

647

Inte

nsity

ratio

(PP

P):4

5.59

5.25

5.75

5.74

5.55

5.42

5.67

5.97

5.93

6.46

5.30

5.97

5.93

6.46

5.30

5.02

5.12

Inte

nsity

ratio

(ME

R):4

7.77

7.29

8.01

8.02

7.77

7.60

7.97

8.43

8.43

9.25

7.64

8.43

8.43

9.25

7.64

7.30

7.51

Em

issi

ons

in S

wed

en d

ue to

exp

orts

:81

218

88 2

7184

498

81 9

9588

650

90 3

7085

853

83 0

7582

578

74 0

0992

676

78 8

9677

753

69 9

7987

007

101

961

102

319

Em

issi

ons

in S

wed

en d

ue to

dire

ct e

xpor

ts:

65 3

2070

602

68 5

2366

175

74 2

5676

585

72 9

2271

650

71 2

4163

263

80 6

3163

363

61 9

0255

395

68 8

2383

587

83 5

63P

hysi

cal t

rade

bal

ance

:5 -9

6 27

1-8

9 92

5-8

6 47

3-7

6 91

0-5

3 59

5-4

9 01

8-4

5 98

9-4

0 65

1-3

4 48

5-4

5 50

9-1

5 90

5-1

16 0

96-1

17 1

20-1

23 3

69-1

15 3

58-1

30 0

37-1

26 3

34P

hysi

cal t

rade

bal

ance

, dire

ct:

-101

335

-104

380

-115

600

-102

428

-101

311

-114

322

-90

494

-73

143

-89

014

-87

714

-58

171

-120

623

-127

776

-131

740

-134

966

-147

015

-152

944

Pro

duct

ion-

base

d em

issi

ons,

incl

. bun

kers

(Sta

tistic

s S

wed

en):

127

546

133

506

121

715

118

233

119

434

122

252

112

915

104

320

102

407

94 1

1311

4 86

910

4 32

010

2 40

794

113

114

869

125

956

125

488

Pro

duct

ion-

base

d em

issi

ons,

exc

l. bu

nker

s (U

NFC

CC

):82

322

80 1

6568

939

66 9

2759

774

56 3

8046

686

41 6

8840

697

40 4

9941

408

41 6

8840

697

40 4

9941

408

36 9

8335

973

NO

xC

onsu

mpt

ion-

base

d em

issi

ons,

tota

l:31

9 88

532

7 03

231

1 12

430

6 16

828

5 88

629

2 02

628

5 14

627

0 31

325

7 49

625

3 39

324

5 08

131

8 40

031

0 91

030

4 13

331

4 31

333

7 72

332

7 96

8

- of

whi

ch is

in S

wed

en:

125

197

125

112

116

365

117

178

108

324

110

208

107

052

98 4

5293

582

91 4

3792

394

107

295

103

384

100

076

104

020

97 3

7195

025

-

abro

ad (P

PP

):2 10

2 46

910

6 38

810

5 19

710

4 57

510

0 68

411

1 20

611

3 58

111

3 13

311

2 10

011

2 80

010

8 17

615

2 37

815

5 71

015

4 90

116

5 78

120

0 10

519

6 34

5

- di

rect

use

:92

219

95 5

3289

561

84 4

1576

878

70 6

1264

513

58 7

2751

815

49 1

5644

512

58 7

2751

815

49 1

5644

512

40 2

4736

598

Em

issi

ons

due

to d

irect

impo

rts (P

PP

):75

316

83 2

9289

125

86 9

5495

609

115

930

105

362

99 5

1011

0 81

710

6 13

910

6 68

712

4 85

813

1 88

713

2 06

315

1 14

718

3 88

719

1 96

3C

onsu

mpt

ion-

base

d em

issi

ons,

tota

l/cap

ita (k

g/ca

p/ye

ar):

2 36

.69

37.2

435

.25

34.6

332

.32

32.9

932

.19

30.4

728

.95

28.3

927

.36

35.8

934

.95

34.0

835

.09

37.5

536

.32

Con

sum

ptio

n-ba

sed

emis

sion

s (M

ER

), to

tal:3

359

954

368

345

352

419

347

650

326

176

336

714

331

294

316

947

304

693

302

005

292

935

381

211

376

467

370

888

387

650

428

573

419

640

Con

sum

ptio

n-ba

sed

emis

sion

s, s

we.

int.,

tota

l:27

8 12

428

5 81

326

7 39

426

2 82

324

3 03

224

2 89

123

4 71

321

7 84

020

4 15

319

5 60

119

4 15

124

7 72

523

6 81

522

4 77

123

6 26

124

4 83

423

4 51

0

- of

whi

ch is

abr

oad:

60 7

0865

169

61 4

6861

230

57 8

3162

072

63 1

4860

660

58 7

5755

008

57 2

4581

703

81 6

1575

539

87 7

2910

7 21

610

2 88

7In

tens

ity ra

tio (P

PP

):4 1.

691.

631.

711.

711.

741.

791.

801.

871.

912.

051.

891.

871.

912.

051.

891.

871.

91In

tens

ity ra

tio (M

ER

):4 2.

352.

272.

382.

392.

442.

512.

532.

632.

712.

932.

732.

632.

712.

932.

732.

712.

80E

mis

sion

s in

Sw

eden

due

to e

xpor

ts:

126

027

141

124

143

737

144

936

160

274

168

278

166

573

165

313

164

718

149

468

177

651

156

426

154

871

140

786

165

997

190

926

190

099

Em

issi

ons

in S

wed

en d

ue to

dire

ct e

xpor

ts:

89 1

9410

0 18

910

1 44

610

2 36

311

8 20

412

5 71

212

3 51

312

3 68

812

3 35

011

0 60

513

7 56

910

8 69

910

6 74

996

222

116

407

140

724

138

862

Phy

sica

l tra

de b

alan

ce:5

23 5

5834

736

38 5

3940

361

59 5

9057

072

52 9

9252

179

52 6

1936

668

69 4

764

048

-840

-14

115

216

-9 1

79-6

246

Phy

sica

l tra

de b

alan

ce, d

irect

:13

878

16 8

9712

322

15 4

0922

596

9 78

218

150

24 1

7812

533

4 46

630

882

-16

159

-25

138

-35

842

-34

740

-43

163

-53

102

Pro

duct

ion-

base

d em

issi

ons,

incl

. bun

kers

(Sta

tistic

s S

wed

en):

343

443

361

768

349

663

346

529

345

476

349

098

338

138

322

492

310

115

290

061

314

557

322

492

310

115

290

061

314

557

328

568

321

745

Pro

duct

ion-

base

d em

issi

ons,

exc

l. bu

nker

s (U

NFC

CC

):27

3 75

027

9 80

026

7 07

626

0 23

324

5 49

223

4 48

922

4 03

421

1 90

820

2 20

719

6 48

819

0 72

521

1 90

820

2 20

719

6 48

819

0 72

518

1 50

517

5 24

0

CO

Con

sum

ptio

n-ba

sed

emis

sion

s, to

tal:

1 20

8 85

71

238

570

1 17

8 74

91

141

887

1 17

2 34

81

219

775

1 12

5 38

01

081

409

1 08

2 32

91

090

522

1 05

1 50

61

070

411

1 07

6 95

41

087

571

1 05

1 25

11

139

088

1 14

5 20

8

- of

whi

ch is

in S

wed

en:

178

059

178

382

164

062

167

003

152

715

148

056

144

764

138

516

135

456

129

651

125

848

141

638

138

634

132

505

129

778

123

553

122

787

-

abro

ad (P

PP

):2 40

5 11

443

9 40

340

0 07

639

3 24

347

5 04

156

9 15

250

7 15

449

0 13

553

1 87

555

3 65

051

7 48

047

6 01

652

3 32

354

7 84

551

3 29

663

2 71

964

3 99

4

- di

rect

use

:62

5 68

462

0 78

661

4 61

058

1 64

154

4 59

250

2 56

747

3 46

245

2 75

841

4 99

740

7 22

140

8 17

845

2 75

841

4 99

740

7 22

140

8 17

838

2 81

637

8 42

7E

mis

sion

s du

e to

dire

ct im

ports

(PP

P):

212

203

236

290

219

765

223

989

283

425

325

567

287

783

279

508

313

802

338

199

313

713

272

753

304

284

332

099

314

063

364

947

387

186

Con

sum

ptio

n-ba

sed

emis

sion

s, to

tal/c

apita

(kg/

cap/

year

):2

139

141

134

129

133

138

127

122

122

122

117

121

121

122

117

127

127

Con

sum

ptio

n-ba

sed

emis

sion

s (M

ER

), to

tal:3

1 36

7 27

01

409

202

1 33

5 79

91

297

874

1 36

2 44

31

448

486

1 33

1 43

71

283

444

1 30

6 26

01

329

121

1 28

0 42

41

266

627

1 29

7 28

31

323

668

1 27

8 31

91

426

351

1 44

5 88

1C

onsu

mpt

ion-

base

d em

issi

ons,

sw

e. in

t., to

tal:

880

674

879

261

851

110

821

911

769

123

728

775

696

352

669

205

629

127

614

254

609

754

670

082

631

039

616

298

613

072

591

138

588

566

-

of w

hich

is a

broa

d:76

931

80 0

9472

437

73 2

6771

816

78 1

5278

126

77 9

3178

673

77 3

8375

728

75 6

8677

408

76 5

7175

116

84 7

6987

352

Inte

nsity

ratio

(PP

P):4

5.27

5.49

5.52

5.37

6.61

7.28

6.49

6.29

6.76

7.15

6.83

6.29

6.76

7.15

6.83

7.46

7.37

Inte

nsity

ratio

(ME

R):4

7.33

7.62

7.69

7.50

9.26

10.2

19.

138.

889.

6110

.24

9.86

8.88

9.61

10.2

49.

8610

.85

10.8

1E

mis

sion

s in

Sw

eden

due

to e

xpor

ts:

90 4

9399

497

100

063

103

817

107

170

101

450

98 5

0696

725

104

020

96 0

5296

411

93 4

2810

0 66

693

040

92 3

7393

042

95 3

24E

mis

sion

s in

Sw

eden

due

to d

irect

exp

orts

:49

990

54 6

1553

939

55 8

8159

284

54 5

1753

020

51 7

8056

974

51 9

8552

741

50 4

3655

780

51 0

8550

691

50 4

5350

394

Phy

sica

l tra

de b

alan

ce:5

-314

621

-339

905

-300

014

-289

426

-367

871

-467

702

-408

648

-393

410

-427

856

-457

598

-421

069

-382

587

-422

657

-454

805

-420

922

-539

677

-548

670

Phy

sica

l tra

de b

alan

ce, d

irect

:-1

62 2

13-1

81 6

75-1

65 8

26-1

68 1

08-2

24 1

41-2

71 0

50-2

34 7

63-2

27 7

29-2

56 8

27-2

86 2

15-2

60 9

72-2

22 3

17-2

48 5

04-2

81 0

14-2

63 3

72-3

14 4

94-3

36 7

92P

rodu

ctio

n-ba

sed

emis

sion

s, in

cl. b

unke

rs (S

tatis

tics

Sw

eden

):89

4 23

889

8 66

587

8 73

585

2 46

180

4 47

775

2 07

371

6 73

268

7 99

965

4 47

363

2 92

463

0 43

768

7 99

965

4 47

363

2 92

463

0 43

759

9 50

059

6 62

7P

rodu

ctio

n-ba

sed

emis

sion

s, e

xcl.

bunk

ers

(UN

FCC

C):

885

905

889

621

867

704

840

100

789

200

723

419

698

693

665

510

627

039

610

987

614

096

665

510

627

039

610

987

614

096

583

675

581

914

116 Excel tables Appendix GY

ear a

nd re

visi

on:

1993

a19

94a

1995

a19

96a

1997

a19

98a

1999

a20

00a

2001

a20

02a

2003

a20

00b

2001

b20

02b

2003

b20

04b

2005

bY

ear (

num

eric

al v

alue

):19

9319

9419

9519

9619

9719

9819

9920

0020

0120

0220

0320

0020

0120

0220

0320

0420

05

NM

VOC

Con

sum

ptio

n-ba

sed

emis

sion

s, to

tal:

319

674

316

764

299

518

293

918

289

412

284

322

274

339

268

462

261

274

263

365

260

030

268

465

262

121

265

210

262

262

282

314

278

581

-

of w

hich

is in

Sw

eden

:47

670

46 8

7143

438

43 9

4237

392

40 4

1038

443

35 2

6533

574

34 4

9732

817

35 9

6834

338

35 1

4333

533

32 0

4630

130

-

abro

ad (P

PP

):2 86

735

89 7

7783

473

87 3

8993

908

94 3

7894

183

100

549

104

007

107

463

104

386

99 8

4910

4 09

010

8 66

310

5 90

112

6 31

012

5 01

3

- di

rect

use

:18

5 26

918

0 11

517

2 60

816

2 58

815

8 11

214

9 53

414

1 71

213

2 64

812

3 69

312

1 40

512

2 82

813

2 64

812

3 69

312

1 40

512

2 82

812

3 95

712

3 43

8E

mis

sion

s du

e to

dire

ct im

ports

(PP

P):

63 3

4162

904

59 2

6661

796

65 3

7962

119

64 5

5770

928

75 8

6681

456

83 5

9570

549

74 8

8781

265

83 2

3890

332

94 3

79C

onsu

mpt

ion-

base

d em

issi

ons,

tota

l/cap

ita (k

g/ca

p/ye

ar):

2 36

.67

36.0

733

.93

33.2

432

.72

32.1

230

.97

30.2

629

.37

29.5

129

.03

30.2

629

.47

29.7

229

.28

31.3

930

.85

Con

sum

ptio

n-ba

sed

emis

sion

s (M

ER

), to

tal:3

353

590

351

627

332

286

328

583

326

991

322

247

312

605

309

909

305

063

309

676

306

208

309

623

305

946

312

039

309

109

339

660

336

948

Con

sum

ptio

n-ba

sed

emis

sion

s, s

we.

int.,

tota

l:26

2 00

325

5 86

624

2 33

723

4 12

022

1 78

621

4 81

420

5 43

119

4 38

318

2 82

018

1 66

818

1 33

419

4 90

318

3 60

518

2 60

218

2 42

318

5 89

418

2 99

0

- of

whi

ch is

abr

oad:

29 0

6428

880

26 2

9227

591

26 2

8224

870

25 2

7526

471

25 5

5325

767

25 6

8926

286

25 5

7326

054

26 0

6229

891

29 4

22In

tens

ity ra

tio (P

PP

):4 2.

983.

113.

173.

173.

573.

793.

733.

804.

074.

174.

063.

804.

074.

174.

064.

234.

25In

tens

ity ra

tio (M

ER

):4 4.

154.

324.

424.

425.

005.

325.

245.

365.

785.

975.

865.

365.

785.

975.

866.

146.

23E

mis

sion

s in

Sw

eden

due

to e

xpor

ts:

35 3

7234

210

33 6

4035

922

35 2

8130

022

31 4

1534

846

33 7

5032

149

33 9

5834

113

32 9

5831

477

33 2

2432

695

32 6

05E

mis

sion

s in

Sw

eden

due

to d

irect

exp

orts

:24

014

22 1

5421

341

23 0

2722

991

18 5

7920

133

23 1

8222

220

21 0

7122

896

22 8

4521

858

20 8

2522

510

22 3

7922

035

Phy

sica

l tra

de b

alan

ce:5

-51

363

-55

568

-49

832

-51

466

-58

627

-64

356

-62

769

-65

703

-70

257

-75

314

-70

427

-65

736

-71

132

-77

185

-72

677

-93

616

-92

408

Phy

sica

l tra

de b

alan

ce, d

irect

:-3

9 32

7-4

0 75

0-3

7 92

6-3

8 77

0-4

2 38

7-4

3 54

0-4

4 42

3-4

7 74

6-5

3 64

6-6

0 38

5-6

0 69

9-4

7 70

4-5

3 02

9-6

0 44

0-6

0 72

8-6

7 95

3-7

2 34

4P

rodu

ctio

n-ba

sed

emis

sion

s, in

cl. b

unke

rs (S

tatis

tics

Sw

eden

):26

8 31

126

1 19

624

9 68

624

2 45

223

0 78

521

9 96

621

1 57

020

2 75

919

1 01

718

8 05

118

9 60

320

2 75

919

1 01

718

8 05

118

9 60

318

8 71

218

6 18

7P

rodu

ctio

n-ba

sed

emis

sion

s, e

xcl.

bunk

ers

(UN

FCC

C):

266

719

259

412

247

494

240

276

229

239

216

708

209

001

200

317

188

477

185

791

187

736

200

317

188

477

185

791

187

736

186

287

183

998

Uni

t: M

illio

n do

llars

/yea

r in

cons

tant

pric

es, T

Wh/

year

(oil,

coa

l, ga

s an

d to

tal f

ossi

l fue

ls) o

r ton

/yea

r (em

issi

ons)

, if n

ot o

ther

wis

e in

dica

ted.

1 N.B

. The

se v

aria

bles

are

in c

urre

nt p

rices

.2 U

sing

wor

ld a

vera

ge in

tens

ities

bas

ed o

n G

DP

PP

P (p

urch

asin

g po

wer

par

ity e

xcha

nge

rate

s).

3 Usi

ng w

orld

ave

rage

inte

nsiti

es b

ased

on

GD

P M

ER

(mar

ket e

xcha

nge

rate

s).

4 Rat

io b

etw

een

the

wor

ld in

tens

ity a

nd th

e S

wed

ish

inte

nsity

.5 U

se o

r em

issi

ons

caus

ed b

y ex

ports

in S

wed

en, l

ess

use

or e

mis

sion

s w

hich

our

dom

estic

fina

l dem

and

caus

es a

broa

d.6 F

or th

e ag

greg

ate

foss

il fu

els

and

CO

2eq,

the

inte

nsity

ratio

s ar

e ca

lcul

ated

afte

rwar

ds s

ince

the

aggr

egat

es a

re b

uilt

upon

ow

n ag

greg

atio

n an

d no

t the

read

y-m

ade

aggr

egat

es a

vaila

ble

in th

e en

viro

nmen

tal a

ccou

nts.

7 The

se e

mis

sion

s ar

e an

agg

rega

te o

f CO

2, C

H4

and

N2O

(wei

ghte

d by

1, 2

1 an

d 31

0 re

spec

tivel

y); t

he re

mai

ning

gre

enho

use

gase

s (H

FCs,

PFC

s an

d S

F6) a

re n

ot in

clud

ed. T

he s

ame

appl

ies

for t

he o

ffici

al U

NFC

CC

val

ue.

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